比特派app中文版下载|phb

作者: 比特派app中文版下载
2024-03-07 20:31:50

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【网络】Cos和ToS和DSCP|Qos|PHB的含义和区别以及映射-CSDN博客

【网络】Cos和ToS和DSCP|Qos|PHB的含义和区别以及映射

bandaoyu

已于 2022-11-04 11:02:45 修改

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于 2021-04-13 14:47:02 首次发布

本文链接：https://blog.csdn.net/bandaoyu/article/details/115666599

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视频教程：

介绍和区别

Qos/Cos

IP-TOS（IPP/CS）和DSCP

PHB（Per-Hop-Behaviors）

区别

各个等级的DSCP值和含义(PHB)

映射

COS到DSCP的映射

IP-Precedence到DSCP的映射（Tos-->DSCP）

详细：

DiffServ 域

Qos分类

PPT

映射实例讲解

Qos 步骤

QOS--理论篇

简略

以太网交换机报文优先级标记：IP Precedence，TOS、DSCP、802.1p prioriy等，适用于不同的QoS 模型

IP Precedence，TOS、DSCP标记位于三层 TOS字段，同一字段不同协议。

802.1p prioriy标记位于二层 TCI字段（Cos是二层ISL或者802.1Q数据帧的优先级标记3个bit，范围0-7）

早期只用TOS 高3个bit标记优先级=》IP Precedence也称IP-TOS、IPP/CS

---》发现组合不够用

增加到用TOS 高6个bit标记优先级 =》DSCP

在实施QoS策略时，Cos与ToS或DSCP之间通常要做映射机制，既二层与三层之间通常要做映射机制。

视频教程：

3、IP QOS区分服务模型详解（PHB、DSCP、COS）_哔哩哔哩_bilibili

介绍和区别

IP优先级、TOS优先级、DSCP优先级和802.1p优先级的区别（802.1P优先级、IP优先级、TOS优先级及DSCP优先级的分类和对应_Mr_zhangtf的博客-CSDN博客_802.1p）

以太网交换机可为特定报文提供优先级标记的服务，优先级的种类包括IP Precedence，TOS、DSCP、802.1p prioriy等，这些优先级分别适用于不同的QoS 模型，在不同的模型中被定义。Precedence、TOS和DSCP优先级是定义在三层IP头中的TOS字段；802.1p用户优先级定义在二层802.1Q 标签头中的TCI字段中。（主要区分TOS字段和TOS ）

IP header 有一个8-bit的TOS（服务类型）优先级区域，它通常被分为precedence部分(IP优先级)和TOS部分，最后一位作保留；它的具体定义如下：

由于对区分服务类型的多样化的要求，在之后的RFC文档中对TOS字段这个区域进行了重新的分配，命名为DSCP：也就是IP包头的区分服务标记域。DSCP优先级是把整个8位的前6位重新定义了一下，称为DSCP优先级；

数据帧里有4个字节的802。1q标签头，包含2字节的标签和2字节的控制信息，在控制信息（vlan tag的TCI区域）的前3位，就定义为802.1p优先级。它指明帧的优先级。一共有8 种优先级，主要用于当交换机阻塞时，优先发送优先级高的数据包。

Qos/Cos

Cos 是在二层。（mac）

QoS（quality of service）是cisco的叫法，类似的叫法，在Juniper为CoS（class of service）。CoS在外企的Juniper设备上配置比较多，在国内用户的设备上见到很少。

IP-TOS（IPP/CS）和DSCP

早期Qos分类简单，使用Tos字段的高3个bit作为TTP的不同组合值（定义IP优先级方案，ip precedence既IPP，称为CS），加起来就八种，后来发现不够，IETF对TOS字段重新分配，提出了DSCP（Differentiated Services Codepoint，区分服务代码点），用6比特取代了原来的3比特。

https://book.51cto.com/art/201012/236881.htm

取值范围0-63，0优先级最低，63优先级最高。COS TOS DHCP通常要做映射机制。

由于DSCP和IP PRECEDENCE是共存的于是存在了一些兼容性的问题，而且DSCP的可读性比较差，比如DSCP 43（101011）我们并不知道对应着IP PRECEDENCE的什么取值，于是就把DSCP进行了进一步的分类。目前定义的DSCP总共分成了4类（64个优先级并未用完）：

类选择器 Class Selector(CS) aaa 000

加速转发 Expedited Forwarding(EF) 101 110

确保转发 Assured Forwarding(AF) aaa bb0

尽力而为 Default(BE) 000 000

https://www.cnblogs.com/zandon/p/11923607.html 新的 DSField 的结构( 差异化服务代码点 + 显示拥塞通知 )：（注意DSField=DSCP+ECN）

IPV4服务类型(TOS)被Differentiated Services Field（DSField）替换_努力不停努力的博客-CSDN博客_differentiated services field

IP-TOS(IPP,IP优先级方案）

DSCP

PHB（Per-Hop-Behaviors）

Per-Hop-Behaviors传输中每一跳的动作。网络管理员可以配置DSCP到PHB的映射。DS采用的缺省PHB是（Best-Effort，DSCP=000000）

Defalut PHB 规定DSCP的后3个bit全为0时，去兼容ip precedence，称为class selector。

区别

TOS和DSCP是三层协议（IP层）中的字段；

COS是二层协议中的字段；

各个等级的DSCP值和含义(PHB)

DSCP不同的值（PHB值）代表选择不同的PHB(Per-Hop Behavior，动作)，PHB代表不同的QoS(时延、带宽等)--->设备根据所选的PHB，为IP报文提供不同的QoS。

每个DSCP值与PHB存在一对一，或多对一的关系。

缺省的PHB编码 000000 对应 Best-effort traffic.

优先级别为CS7>CS6>EF>AF31>(AF32,AF31)>AF11>(AF12,AF13)>BE,通俗定义为CS7>CS6>EF>AF4>AF3>AF2>AF1>BE.通常CS级别为网络内部协议使用，所以最高级别为EF

映射

COS到DSCP的映射(二层与三层之间的映射）

（QOS中DSCP/COS/IP的映射关系_网络工程师的技术博客_51CTO博客）

默认关系如下：

查看命令：

这是个二维阵列表，d1 列代表DSCP值的十位数，d2 行代表DSCP值的个位数。在列与行交叉的位置上显示的是映射到该DSCP值上的CoS值。

比如DSCP值08(十进制）（D1=0，D2=8）交叉值是01，就表示对应的COS 值是01.

再比如

比如DSCP值0x30=48-->(D1=4,D2=8)

IP-Precedence到DSCP的映射（Tos-->DSCP，不同三层之间的映射）

默认的IP-Precedence-to-DSCP映射关系如下。

802.1P优先级、IP优先级、TOS优先级及DSCP优先级的分类和对应_Mr_zhangtf的博客-CSDN博客_802.1p

详细：

DiffServ 域

TOS/DSCP/COSl区别与联系 - osc_pmgs5uax的个人空间 - OSCHINA - 中文开源技术交流社区

TOS在不同协议中进行过定义，分别为RFC791、RFC1122、RFC1349；RFC1349废除了之前两个RFC定义，现在大多数设备使用RFC1349.

DSCP由RFC2474定义，重新命名了IPv4包头中TOS和IPv6包头中数据类(Traffic Class)那1字节，新的名称为DS字段，仍然被QoS工具用来标注数据。

0 1 2 3 4 5 6 7 +---+---+---+---+---+---+---+---+ | DSCP | CU | +---+---+---+---+---+---+---+---+ DSCP: differentiated services codepoin CU: currently unused

COS在802.1q标准定义，在二层数据帧(802.1q帧)里包含2个字节的标签(TPID)和2个字节的控制信息(TCI)，TCI的前3位定义了802.1p优先级。

在实施Qos策略时，Cos与Tos或DSCP之间通常要做映射机制。

Qos分类

《理解DSCP PHB AF DF》：芋头和红薯哪个热量高-秋后算账网

PPT

上图的CS等级

DSCP-PHB行为的AF类，规定前3bit不能为101且最后一个bit为0的任意组合，前3bit的组合为类，跟着的2bit为dd域，所以

所以有AF类有AF1-AF4，4个类。配合dd则为AF1-dd

AF1-01（AF11） AF2-01（AF21）AF3-01（AF31） AF1-02（AF12） AF2-02（AF22）AF3-02（AF32） AF1-03（AF13） AF2-03（AF23）AF3-03（AF33）

AF类消息定义发送拥塞时被丢弃的可能，dd=Low 低概率，Medium 中概率，High 最先被丢弃

映射实例讲解

Traffic class 0xc0==>CS6==>DSCP 0x30

Qos 步骤

根据需要-->保证带宽/最小延迟……-->标志-->查

http://www.inotes.cn/Cx/page/inote/3-3

QOS--理论篇

关于qos ，也是linux下面必备功能之一，一般只需要结合iptables/etables/iproute2 和tc配合即可实现大部分功能. 网上讲这么方面的资料很多，大部分都讲tc命令的应用.这里就先从理论入手. QoS（Quality of Service）服务质量，是网络的一种安全机制, 是用来解决网络延迟和阻塞等问题的一种技术。但是对关键应用和多媒体应用就十分必要。当网络过载或拥塞时，QoS 能确保重要业务量不受延迟或丢弃，同时保证网络的高效运行. 在网络总带宽固定的情况下，如果某类业务占用的带宽越多，那么其他业务能使用的带宽就越少，可能会影响其他业务的使用。因此，网络管理者需要根据各种业务的特点来对网络资源进行合理的规划和分配，从而使网络资源得到高效利用 QoS服务模型通常QoS提供以下三种服务模型： 1> Best-Effort service（尽力而为服务模型）（系统默认；PFIFO_FAST） 2> Integrated service（综合服务模型，简称Int-Serv） 3>Differentiated service（区分服务模型，简称Diff-Serv）　1. Best-Effort服务模型Best-Effort是一个单一的服务模型，也是最简单的服务模型。对Best-Effort服务模型，网络尽最大的可能性来发送报文。但对时延、可靠性等性能不提供任何保证。　　Best-Effort服务模型是网络的缺省服务模型，通过FIFO队列来实现。它适用于绝大多数网络应用，如FTP、E-Mail等。　2. Int-Serv服务模型Int-Serv是一个综合服务模型，它可以满足多种QoS需求。该模型使用资源预留协议（RSVP），RSVP运行在从源端到目的端的每个设备上，可以监视每个流，以防止其消耗资源过多。这种体系能够明确区分并保证每一个业务流的服务质量，为网络提供最细粒度化的服务质量区分。　　但是，Inter-Serv模型对设备的要求很高，当网络中的数据流数量很大时，设备的存储和处理能力会遇到很大的压力。Inter-Serv模型可扩展性很差，难以在Internet核心网络实施，前主要与MPLS TE（Traffic Engineering，流量工程）结合使用. 3. Diff-Serv服务模型Diff-Serv是一个多服务模型，它可以满足不同的QoS需求。与Int-Serv不同，它不需要通知网络为每个业务预留资源。区分服务实现简单，扩展性较好，可以说是为现在的网络量身打做的。这个这种类型的QOS中，数据流是要进行分类的，然后，我们可以进一步的对各种不同类的流进行的控制。这个控制的实现就是通过策略表来实现的。这样简单一说，我们就该知道了，实现他们是要有个类表，然后还得有个控制表---策略表. 它由RFC2475定义，在区分服务中，根据服务要求对不同业务的数据进行分类，对报文按类进行优先级标记，然后有差别地提供服务。区分服务一般用来为一些重要的应用提供端到端的QoS，它通过下列技术来实现： 1）流量标记与控制技术：它根据报文的CoS（Class of Service，服务等级）域、ToS域（对于IP报文是指IP优先级或者DSCP）、IP报文的五元组（协议、源地址、目的地址、源端口号、目的端口号）等信息进行报文分类，完成报文的标记和流量监管。目前实现流量监管技术多采用令牌桶机制。 2）拥塞管理与拥塞避免技术：WRED、PQ、CQ、WFQ、CBQ等队列技术对拥塞的报文进行缓存和调度，实现拥塞管理与拥塞避免。 QoS的应用　　流量约定（SLA, Service Level Agreement服务等级协议）给数据流设定优先级，以此在网络／协议层面上，根据相互商定的尺度，设定有保障的性能、通过量、延迟等界限。一些特定形式的网络数据流需要定义服务质量，例如：　　多媒体流要求有保障的通过量　　IP电话需要严格的抖动和延迟限制　　性命攸关的应用系统，例如远程外科手术要求有可靠保证的可用性（也称作硬性　QoS）. 这些类型的服务被称为非弹性，意思是它们需要固定的带宽才能运作--如果得到多余的带宽，它们也无法使用；如果得到较少的带宽，则根本无法工作。相形之下，弹性应用可以从多余的带宽中受益。网络中会遇到的情况： 1. 数据包丢失当数据包到达一个缓冲器（buffer）已满的路由器时，则代表此次的发送失败，路由器会依网络的状况决定要丢弃一部份、不丢弃或者是所有的数据包，而且这不可能在预先就知道，接收端的应用程序在这时必须请求重新传送，而这同时可能造成总体传输严重的延迟 2. 延迟或许需要很长时间才能将数据包传送到终点，因为它会被漫长的队列迟滞，或需要运用间接路由以避免阻塞；也许能找到快速、直接的路由。总之，延迟非常难以预料 3. 传输顺序出错当一群相关的数据包被路由经过因特网时，不同的数据包可能选择不同的路由器，这会导致每个数据包有不同的延迟时间。最后数据包到达目的地的顺序会和数据包从发送端发送出去的顺序不一致，这个问题必须要有特殊额外的协议负责刷新失序的数据包。 4. 出错有些时候，数据包在被运送的途中会发生跑错路径、被合并甚至是毁坏的情况，这时接收端必须要能侦测出这些情况，并将它们统统判别为已遗失的数据包，再请求发送端再送一份同样的数据包。处理流程：分类 Classifying即分类，其过程是根据信任策略或者根据分析每个报文的内容来确定将这些报文归类到以CoS值来表示的各个数据流中，因此分类动作的核心任务是确定输入报文的CoS值。分类发生在端口接收输入报文阶段，当某个端口关联了一个表示QoS策略的Policy-map后，分类就在该端口上生效，它对所有从该端口输入的报文起作用 (1)协议有些协议非常“健谈”，只要它们存在就会导致业务延迟，因此根据协议对数据包进行识别和优先级处理可以降低延迟。应用可以通过它们的EtherType进行识别。譬如，AppleTalk协议采用0x809B，IPX使用0x8137。根据协议进行优先级处理是控制或阻止少数较老设备所使用的“健谈”协议的一种强有力方法。

（2） TCP和UDP端口号码许多应用都采用一些TCP或UDP端口进行通信，如HTTP采用TCP端口80。通过检查IP数据包的端口号码，智能网络可以确定数据包是由哪类应用产生的，这种方法也称为第四层交换，因为TCP和UDP都位于OSI模型的第四层。 (3) 源IP地址许多应用都是通过其源IP地址进行识别的。由于服务器有时是专门针对单一应用而配置的，如电子邮件服务器，所以分析数据包的源IP地址可以识别该数据包是由什么应用产生的。当识别交换机与应用服务器不直接相连，而且许多不同服务器的数据流都到达该交换机时，这种方法就非常有用。 (4) 物理端口号码与源IP地址类似，物理端口号码可以指示哪个服务器正在发送数据。这种方法取决于交换机物理端口和应用服务器的映射关系。虽然这是最简单的分类形式，但是它依赖于直接与该交换机连接的服务器策略 Policing 即策略，发生在数据流分类完成后，用于约束被分类的数据流所占用的传输带宽。Policing动作检查被归类的数据流中的每一个报文，如果该报文超出了作用于该数据流的Police所允许的限制带宽，那么该报文将会被做特殊处理，它或者要被丢弃，或者要被赋予另外的DSCP 值。在QoS 处理流程中，Policing 动作是可选的。如果没有Policing 动作，那么被分类的数据流中的报文的DSCP 值将不会作任何修改，报文也不会在送往Marking 动作之前被丢弃。标识 Marking即标识，经过Classifying 和Policing 动作处理之后，为了确保被分类报文对应DSCP的值能够传递给网络上的下一跳设备，需要通过Marking 动作将为报文写入QoS 信息，可以使用QoS ACLs 改变报文的QoS信息，也可以使用Trust 方式直接保留报文中QoS 信息，例如，选择Trust DSCP 从而保留IP 报文头的DSCP 信息。队列 Queueing即队列，负责将数据流中报文送往端口的某个输出队列中，送往端口的不同输出队列的报文将获得不同等级和性质的传输服务策略。每一个端口上都拥有8 个输出队列，通过设备上配置的DSCP-to-CoS Map 和Cos-to-Queue Map 两张映射表来将报文的DSCP 值转化成输出队列号，以便确定报文应该被送往的输出队列。调度 Scheduling即调度，为QoS 流程的最后一个环节。当报文被送到端口的不同输出队列上之后，设备将采用WRR 或者其它算法发送8 个队列中的报文。可以通过设置WRR算法的权重值来配置各个输出队列在输出报文的时候所占用的每循环发送报文个数,从而影响传输带宽。或通过设置DRR算法的权重值来配置各个输出队列在输出报文的时候所占用的每循环发送报文字节数,从而影响传输带宽

先说说常用的分类和标记，首先需要说下： cos tos dscp的概念及区别: 1、COS是在第二层ISL或802.1Q数据帧中的ISL或802。1Q的报头中的3位用于COS，即优先标识。3bit，0--7个级别。 802.1Q: 2、TOS是在第三层IP数据包中的8位TOS数据位，以来标识优先级。这8位中前3位表示优先级，后4位表示服务类型(分别为：最小延迟、最大吞吐量、最高可靠性、最小费用。只能其中一位为1，即生效。如果全为0就表示一般服务）。最后一位一般不用，置0 3、DSCP也是三层IP中的8位TOS字段表示优先级。不同的是用了前6位表示优先级，可设0--63，共64个等级。（把前6位中的前3位设为优先级，后3位设为0，就可以实现DSCP和TOS互相映射兼容）。最后两位为早期拥塞通知。因为COS二层标记中也是3位用于优先级，所以也可以把COS和TOS和DSCP中的优先级映射 DSCP数位域标识出数据包所属的特定交付分类，具体实现方法是企业为分类制定明确的交付目标。路由器和其它设备可以通过数据包队列（本质上就是缓冲区）和相应算法，传递数据包，实现交付目标。一些推荐标准涉及到DSCP数位域的值（如RFC2474中列举的），它们围绕加速转发（进一步描述可参见RFC3246）和确保转发（RFC2597）定义了一些期望行为：加速转发让交付过程低丢包、低延时和抖动最小；确保转发则保证无损交付。

RFC推荐使用DSCP值46来标记加速转发分类（6位DSCP的二进制值为101110），它适用于诸如VoIP或IP会议的实时交互多媒体流；为确保转发流量分配了包含12个标记值的集合，来保证不同等级的交付。

这里cos和dscp是修改了数据报文的内容，可以在网络其他设备来调度，还有本地主机的工具可以打一些标记，tc的u32模块，iptables的MARK，以及iproute2的工具. 这些工具并不修改报文，而是提供本地内核调度用. QOS要保证服务，就要设计流量控制我们先了解几个概念：流量控制中的概念 1. 整形整形就是流量控制，把数据包的发送速率控制在一个固定的水平以下。由于整形通过延迟数据包的发送来控制数据包发送速率，故整形机制是非工作保存的。“非工作保存”可以理解为：系统必须进行一些操作来延迟数据包的发送。反过来说，一种非工作保存的队列是可以进行流量整形的，而工作保存的队列（参考 PRIO）不能进行流量整形，因为工作保存队列无法延迟发送数据包。 2. 调度一个调度器会对将要发送的数据包顺序进行排列或重排。 3分类分类器能把不同类型的网络流量划分到不同的队列中去。 4.策略决策器能计算并限制某个特定队列的流量 4. 丢弃丢弃一个数据包，一个数据流或一个分类下的数据包，都可以叫做丢弃。 5. 标记标记是一种对数据包进行一些修改的操作注意这里说的标记不是fwmark。iptables，$ipt-mark;，ipchains以及--mark都只修改数据包的元数据，而不修改数据包本身。流量控制中的标记操作会给数据包加上一个DSCP，接下来在由一个管理员控制的一个网络下的其他路由器上将会使用这个标记。QoS的关键指标主要包括：可用性、吞吐量、时延、时延变化(包括抖动和漂移)和丢失在linux中是通过Tc命令来实现的（外加内核的支持）. 我们看到网上大部分说的队列规则、分类、分类器什么的都是说的TC的机制，而tc只是实现qos的方式之一. 在网络通信设备中不同的厂商对qos有各自的实现和配置. 基于QOS的特性，便产生了tc. 我们先看一个图：关于tc的设计：递归控制所谓的递归控制就是分层次地控制，而对于每个层次，控制方式都是一致的 Qdisc –class –filter 的树型组织模式.qdisc 队列规则(queueing discipline): 用来实现控制网络的收发速度.通过队列,linux可以将网络数据包缓存起来,然后根据用户的设置,在尽量不中断连接(如 tcp)的前提下来平滑网络流量.需要注意的是,linux 对接收队列的控制不够好,所以我们一般只用发送队列,即"控发不控收".它封装了其他两个主要 tc 组件(类和分类器).内核如果需要通过某个网络接口发送数据包,它都需要按照为这个接口配置的 qdisc 队列规则把数据包加入队列.然后,内核会尽可能多地从 qdisc里面取出数据包,把它们交给网络适配器驱动模块. 最简单的 QDisc 是 pfifo 它不对进入的数据包做任何的处理,数据包采用先入先出的方式通过队列.不过,它会保存网络接口一时无法处理的数据包.常有的队列规则包括 FIFO 先进先出,RED 随机早期探测,SFQ 随机公平队列和令牌桶 Token Bucket,类基队列 CBQ,CBQ 是一种超级队列,即它能够包含其它队列,甚至其它 CBQClass 类 class 用来表示控制策略.很显然,很多时候,我们很可能要对不同的IP实行不同的流量控制策略,这时候我们就得用不同的class来表示不同的控制策略了.Filter 规则 filter 用来将用户划入到具体的控制策略中目前,tc可以使用的过滤器有：fwmark分类器,u32 分类器,基于路由的分类器和 RSVP 分类器（分别用于IPV6、IPV4）等；其中,fwmark 分类器允许我们使用 Linux netfilter 代码选择流量,而 u32 分类器允许我们选择基于 ANY 头的流量 .需要注意的是,filter (过滤器)是在QDisc 内部,它们不能作为主体

关于tc的具体应用，我们以后分析.这里仅仅以理论作为引导让我们了解什么是QOS.

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【网络】Cos和ToS和DSCP|Qos|PHB的含义和区别以及映射

目录Qos/Cos：IP-TOS和DSCP区别：详细：TOS-DSCP 对照表更多：Qos/Cos：QoS（quality of service）是cisco的叫法，类似的叫法，在Juniper为CoS（class of service）。CoS在外企的Juniper设备上配置比较多，在国内用户的设备上见到很少。IP-TOS和DSCP（IP优先级方案）ToS是历史产物，有点简单粗暴，只有三位二进制数，加起来就八种，后来发现不够，IETF提出了DSCP（Differen

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qos的类型和详细介绍

02-01

cos、802.1p、tos、dscp的解释和分析

IP Qos DSCP和TOS分类

04-22

IP Qos DSCP和TOS分类

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华为HCIE课堂笔记第十六章 Qos基本原理

生物基生物降解材料聚羟基烷酸酯（PHA）的介绍 - 知乎

生物基生物降解材料聚羟基烷酸酯（PHA）的介绍 - 知乎切换模式写文章登录/注册生物基生物降解材料聚羟基烷酸酯（PHA）的介绍塑金买卖塑料上塑金、更放心！www.52abs.com1、PHA概述基本介绍聚羟基烷酸酯( polyhydroxyalkanoates 简称PHA) ，PHA是由微生物通过各种碳源发酵而合成的不同结构的脂肪族共聚聚酯，其基本结构如下图。 PHA具有不同的单体结构，因此种类繁多。既有由短链单体组成的PHA，也有由中长链单体组成的PHA，还有由不同种类单体组成的共聚物。其中最常见的有聚3-羟基丁酸酯(PHB)、聚羟基戊酸酯(PHV)及PHB和PHV的共聚物(PHBV)。由于 PHA单体种类繁多，彼此之间链长差别很大，造成不同 PHA的材料学性质也大不相同（如下图）。买卖塑料，上塑金在线。更放心不同种类PHA和通用塑料的物理性能对比PHA的发展史PHA的研究，从1925年被一个叫Lemoigne的法国人发现而开始，他首次在巨大芽孢杆菌（Bacillus megaterium）中发现了一种后来被命名为聚3-羟基丁酸（缩写为PHB，为PHA家族中的一员）的天然高分子。 PHB是PHA家族中拥有“最”头衔最多的成员，如最早被发现（1926年被发现）、结构最简单、最常见（大部分天然的PHA都含有PHB的成分）等等。1958年williamson用微生物巨大芽孢杆菌，通过葡萄糖发酵，高效合成了聚-β-羟基丁酸酯。1980年英国帝国化学公司（ICI）（后改为Zeneca）公司从戊酮和葡萄糖出发，用微生物产碱杆菌发酵合成了以β-羟基丁酯和β-羟基戊酯为聚合单元的共聚物—聚（β-羟基丁酯/β-羟基戊酯）共聚物[P（β-HB-co-β-HV），P（3-HB-co-3-HV）]。国内对PHA 的研究开始较早，并得到了科技部重大科技项目以及国家自然基金委、国家发改委等的研究支持，经过多年的投入，技术已处于世界领先水平，曾利用现代基因工程技术，在世界上首次实现了基因工程菌生产聚β‑羟基丁酸（PHB）和3‑羟基丁酸与3‑羟基己酸的共聚酯（PHBHHx）。 PHA的生物合成路线微生物代谢的多样性决定了合成PHA的路线也不尽相同，基质的变化也会使其合成路线出现差异，下图为一些微生物利用不同基质合成PHA的主要途径。在不同微生物中从不同基质合成PHA的主要途径①真养产碱杆菌及多数细菌从糖合成PHB；②深红红螺菌从糖合成PHB；③食油假单胞菌等从中链烷、醇及酸合成PHAs；④一株产碱杆菌从长链偶碳数脂肪酸合成PHB；⑤铜绿假单胞菌等从糖质碳源(如葡萄糖酸)合成PHA；⑥真养产碱杆菌等利用糖+丙酸合成PHBVPHA的降解机理PHA的降解机理可以间接地指明产品的应用方向和最终处理方法，下面以PHB为例简述其降解机理，PHB的降解分为两种，一种是胞内分解，一种是胞外分解。①胞内分解PHB在细胞内的分解是一个以营养条件为变化依据的循环过程，当营养失衡又有碳源存在时，细胞就会大量积累PHB，而当营养重新平衡时, PHB又会被分解，PHB的代谢途径如下图所示。 PHB分子链的分解是从外端即羟基端开始的，在PHB代谢中，最关键的酶是3-酮硫酯酶，它是一个双向调控酶，既参与合成有参与分解。②胞外分解PHB的水解(不排除其植入人体后诱导其产生物分解酶酶解的可能性)对其作为生物医用材料的应用(如手术缝线、骨针、骨板、药物缓释载体等)非常重要。与聚乳酸的水解完全不同, PHBV的水解是从表面开始逐渐往内进入,而聚乳酸却是内外同时水解。PHB在环境中的分解主要为酶分解。通常情况下, PHB出现在环境中后,经过一定的迟滞期,微生物生成的PHB解聚酶会逐渐增多,活力升高,分解速率也会明显加快。PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777PHB在不同环境条件下的生物分解环境条件1mm厚膜消失所需时间/周分解速度/（μm/周）50μm厚膜消失所需时间/周分解速度/（μm/周）厌气活性污泥61700.5100河口堆积物4025510土壤（25℃）7513105海水（℃）3502.5501好气活性污泥601777 2、PHA性能与应用 PHA的性能作为一种天然的高分子材料，PHA当然具有常见高分子的基本特征，如热可塑性或可热加工性。同时，PHA还具有一些特殊的材料学特征，如：非线性光学活性、压电性、气体阻隔性等，其基本性能与聚丙烯相似。最重要的是，PHA作为一种生物材料，还具有非常重要的两大属性：（1）良好的生物可降解性（2）良好的生物相容性 PHA的应用正因为PHA有千奇百怪的支链，所以这一家族也汇集了众多的优良性能，其潜在的应用领域也是五花八门。目前已知的PHA可用于医疗、药物、化妆品等高附加值领域，也在环保包装材料、喷涂材料、衣料服装、器具类材料、电子通信、快速消费品、农业产品、自动化产品、化学介质等领域有广泛的应用前景。随着PHA多样性的日益拓宽, PHA的应用领域也必然越来越广。然而PHA的大规模产业化和商业化一直受到生产成本的制约,特别是新型PHA的生产成本大大高于传统PHA,在一定程度上限制了对其应用研究的开展。通过合成与系统生物学、蓝水生物技术等手段整合各种PHA的合成,实现一种底盘菌、多个代谢途径、按需合成某一种的PHA低成本生产平台,最终将有可能降低所有种类PHA的生产成本,从而促进不同类型PHA应用于不同领域。在环保政策的驱动下，PLA、PBAT、PHA、PCL、PBS等生物降解塑料，在一次性餐具、包装、农业、汽车、医疗、纺织等领域的应用正迎来市场发展新机遇。生物降解塑料的改性材料，以及相关助剂，如扩链接，抗水解剂，增韧剂，成核剂，抗菌剂也会有新一轮的创新。发布于 2020-09-04 11:26塑料降解赞同 236 条评论分享喜欢收藏申请

聚羟基丁酸酯（PHB）性能不断提升应用领域有望扩展 - 知乎

聚羟基丁酸酯（PHB）性能不断提升应用领域有望扩展 - 知乎首发于新思界行业研究切换模式写文章登录/注册聚羟基丁酸酯（PHB）性能不断提升应用领域有望扩展新思界聚羟基丁酸酯（PHB）性能不断提升应用领域有望扩展　　聚羟基丁酸酯（PHB）是一种以3HB为单体的短链均聚物，属于结晶型材料。聚羟基丁酸酯是聚羟基脂肪酸酯（PHA）主要类型之一，与PHBV等其他PHA类型相比，聚羟基丁酸酯的强度较高，但其加工性能、韧性较差。聚羟基丁酸酯熔点接近热分解温度，因此热加工窗口较窄，主要用于注塑、纤维等。　　根据新思界产业研究中心发布的《2023-2027年聚羟基丁酸酯（PHB）行业深度市场调研及投资策略建议报告》显示，聚羟基丁酸酯具有高结晶度，结构规整、质硬而脆，现阶段，全球从事聚羟基丁酸酯研究和生产的企业有美国New light公司、天安生物、意大利Bio-on、中粮生化、Biomers、珠海麦得发生物科技、北京微构工场等。　　聚羟基丁酸酯生物相容性好，具有可生物降解特性，在医用材料、可降解塑料、一次性餐具、眼镜框、包装、污水处理、玩具等领域具有广阔应用前景。在医用材料领域，聚羟基丁酸酯可用于制备药物缓释载体材料、组织工程材料等；在包装领域，聚羟基丁酸酯降解产物主要为二氧化碳和水，符合当下绿色、环保发展观念，未来应用潜力巨大。　　在全球范围内，日本、美国、韩国等国家聚羟基丁酸酯技术较为先进，应用场景广泛。在生产方面，微生物发酵法是聚羟基丁酸酯主要生产工艺。聚羟基丁酸酯生物相容性好，但材料脆性大、热稳定性差，近年来，为扩大应用场景，国内外企业开始对聚羟基丁酸酯材料进行改良，如添加PSPH聚合物、增加第二单体形式等。　　聚羟基脂肪酸酯（PHA）是由微生物通过各种碳源发酵而合成的不同结构的脂肪族共聚聚酯。PHA于上世纪末开始产业化生产，但由于生产成本高，PHA产业化进程缓慢，但基于PHA广阔应用前景，全球PHA研发热情较高。目前PHA已升级到第四代，分别为PHB、PHBV、PHBHHx、P34HB。随着相关技术进步，PHA产业规模不断扩大，预计十四五期间，我国PHA规划产能将达到45万吨左右。　　新思界行业分析人士表示，聚羟基丁酸酯是商业化最早的PHA类型，凭借生物相容性好、可生物降解等特点，聚羟基丁酸酯在包装、医用材料等领域展现出良好应用前景。聚羟基丁酸酯热稳定性差，限制了其市场应用，但随着改性研究不断深入，聚羟基丁酸酯性能在不断提升，未来应用范围有望进一步扩展。2023-2027年聚羟基丁酸酯（PHB）行业深度市场调研及投资策略建议报告报告目录报告目录节选。。。三章聚羟基丁酸酯（PHB）产品市场供需分析第一节聚羟基丁酸酯（PHB）市场特征分析一、产品特征二、价格特征三、渠道特征四、购买特征第二节聚羟基丁酸酯（PHB）市场需求情况分析第三节聚羟基丁酸酯（PHB）市场供给情况分析第四节聚羟基丁酸酯（PHB）市场供给平衡性分析第四章聚羟基丁酸酯（PHB）行业供需现状分析第一节聚羟基丁酸酯（PHB）行业总体规模第二节聚羟基丁酸酯（PHB）产能概况第三节聚羟基丁酸酯（PHB）产量概况一、产量变动二、产能配置与产能利用率调查第五章聚羟基丁酸酯（PHB）行业产业链发展分析第一节聚羟基丁酸酯（PHB）行业产业链模型分析第二节聚羟基丁酸酯（PHB）行业上（下）游行业发展概况第三节聚羟基丁酸酯（PHB）行业原材料供给情况第四节聚羟基丁酸酯（PHB）行业下游消费市场构成第六章聚羟基丁酸酯（PHB）原材料供应情况分析第一节聚羟基丁酸酯（PHB）主要原材料构成分析第二节聚羟基丁酸酯（PHB）主要原材料产量变动情况第三节聚羟基丁酸酯（PHB）主要原材料价格变化趋势分析第七章聚羟基丁酸酯（PHB）行业用户分析第一节用户认知程度第二节用户关注因素一、功能二、产品质量三、价格四、产品设计第三节用户其它特性第八章聚羟基丁酸酯（PHB）国内重点生产企业分析第一节公司1 一、公司基本情况二、公司产品竞争力分析三、公司投资情况四、公司未来战略分析第二节公司2 一、公司基本情况二、公司产品竞争力。。。发布于 2023-01-06 10:28・IP 属地河南化学有机化学可行性研究报告赞同 2添加评论分享喜欢收藏申请转载文章被以下专栏收录新思界行业研究新思界，市场调查、行业研究、规划咨询的国内

聚羟基脂肪酸酯PHA代谢工程研究30年

生物工程学报 2021, Vol. 37 Issue (5): 1794-1811

http://dx.doi.org/10.13345/j.cjb.200457

中国科学院微生物研究所、中国微生物学会主办

文章信息

陈心宇, 李梦怡, 陈国强

Chen Xinyu, Li Mengyi, Chen Guo-qiang

聚羟基脂肪酸酯PHA代谢工程研究30年

Thirty years of metabolic engineering for biosynthesis of polyhydroxyalkanoates

生物工程学报, 2021, 37(5): 1794-1811

Chinese Journal of Biotechnology, 2021, 37(5): 1794-1811

10.13345/j.cjb.200457

文章历史

Received: July 26, 2020

Accepted: October 13, 2020

Published: November 19, 2020

Abstract

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引用本文

陈心宇, 李梦怡, 陈国强, 等. 聚羟基脂肪酸酯PHA代谢工程研究30年. 生物工程学报, 2021, 37(5): 1794-1811

Chen XY, Li MY, Chen GQ, et al. Thirty years of metabolic engineering for biosynthesis of polyhydroxyalkanoates. Chinese Journal of Biotechnology, 2021, 37(5): 1794-1811.

聚羟基脂肪酸酯PHA代谢工程研究30年

陈心宇

李梦怡

陈国强

清华大学生命科学学院化工系，北京 100084

收稿日期：2020-07-26；接收日期：2020-10-13；网络出版时间：2020-11-19

基金项目：国家重点研发计划(No. 2018YFA0900200)，国家自然科学基金(Nos. 31961133019, 21761132013, 31870859) 资助

作者简介：陈国强清华大学生命学院化工系教授。《生物工程学报》第3–5届副主编。长期从事微生物合成生物学、微生物PHA材料合成及以极端细菌为基础的“下一代工业生物技术”的研究，获得相关授权专利35项和45项公开专利。开发的技术已经在数家公司用于大规模生产微生物塑料聚羟基脂肪酸酯PHA。曾连续6年获得清华大学学生“良师益友”的光荣称号。在国际学术期刊上共发表微生物技术和生物材料相关论文350多篇，论文在Web of Sciences上被引用19 000余次(H指数为67).

摘要：聚羟基脂肪酸酯(Polyhydroxyalkanoate，PHA) 是微生物合成的可降解高分子材料，种类及性能多样，应用前景广阔，然而其大规模生产受制于它较为高昂的生产成本。30年来，代谢工程的应用日益广泛，通过代谢流调控、代谢通路改造引入新通路等方法，微生物合成PHA的效率得到了很大提高，也丰富了PHA的单体种类、结构多样性和底物多样性；同时通过改变细胞形态和PHA颗粒大小等方法实现了更加高效的下游生产处理，降低了PHA生产成本。近年来，基于极端微生物，尤其是嗜盐菌的“下一代工业生物技术” (Next generation industrial biotechnology，NGIB) 发展迅速。NGIB实现了PHA生产过程的开放性和连续性，节约能源和淡水，简化了PHA的生产过程。结合代谢工程技术，盐单胞菌可以作为多种PHA的低成本生产平台，将有望提高PHA的市场竞争力和推进其商业化。

关键词：聚羟基脂肪酸酯合成生物学代谢工程下一代工业生物技术

Thirty years of metabolic engineering for biosynthesis of polyhydroxyalkanoates

Xinyu Chen

Mengyi Li

Guo-qiang Chen

School of Life Science, Department Chemical Engineering, Tsinghua University, Beijing 100084, China

Received: July 26, 2020; Accepted: October 13, 2020; Published: November 19, 2020

Supported by: National Key Research and Development Program of China (No. 2018YFA0900200), National Natural Science Foundation of China (Nos. 31961133019, 21761132013, 31870859)

Corresponding author:

Guo-qiang Chen. Tel: +86-10-62783844; Fax: +86-10-62794217; E-mail: chengq@mail.tsinghua.edu.cn.

*These authors contributed equally to this study.

Abstract: Polyhydroxyalkanoate (PHA) is a family of biodegradable polyesters synthesized by microorganisms. It has various monomer structures and physical properties with broad application prospects. However, its large-scale production is still hindered by the high cost. In the past 30 years, metabolic engineering approach has been used to tune the metabolic flux, engineer and introduce pathways. The efficiency of PHA synthesis by microorganisms has been significantly improved, and the diversity of PHA monomer, structure and substrate have also been enriched. Meanwhile, by changing cell morphology and PHA particle size, more efficient downstream production process has achieved and PHA production costs have been reduced. In recent years, "Next generation industrial biotechnology" (NGIB) based on extremophiles, especially halophilic Halomonas spp., has been rapidly developed. NGIB has achieved the opening and continuous production of PHA, which simplifies the production process and saves energy and fresh water. Combined with metabolic engineering, Halomonas spp. can be transformed into low-cost production platform of numerous PHA. It is expected to improve the market competitiveness and promote the commercialization of PHA.

Keywords:

polyhydroxyalkanoates synthetic biology metabolic engineering next generation industrial biotechnology

聚羟基脂肪酸酯(Polyhydroxyalkanoates，PHA) 是一类生物合成的高分子聚酯的统称，是部分微生物(主要是细菌) 在营养或代谢不平衡的条件下合成的一种储能物质[1]。PHA具有良好的生物可降解性和生物相容性，被公认为绿色环保型高分子材料；且由于其种类和性能的多样性，可被应用于大宗塑料、医学材料、生物燃料甚至饲料等诸多领域而受到广泛关注[2-5]。近年来随着代谢工程技术的发展，关于PHA的微生物合成也有了新的突破。本文介绍了近30年应用代谢工程技术拓展PHA的多样性、改造PHA合成相关通路、提高PHA合成效率、进行PHA的低成本生产等方面的进展，重点介绍以嗜盐单胞菌为底盘的“下一代工业生物技术”并提出展望。

1 PHA多样性及合成途径

1.1 PHA的单体组成及分类自20世纪20年代首次在微生物细胞内发现PHB (聚3-羟基丁酸，最常见的PHA) 以来[6]，不断有新的PHA在不同的微生物菌体中被合成出来，目前已有超过150种PHA被研究报道[7]。PHA化学本质上是一种高分子聚酯，在细胞体内PHA聚合酶(PhaC) 的催化下，一定碳链长度的羟基脂肪酸相互连接形成酯键，最终形成不同类型、不同分子量的PHA聚酯[8]。

根据组成单体碳链长度的不同，PHA可以分为短链PHA (Short chain length PHA，SCL PHA)和中长链PHA (Medium chain length PHA，MCL PHA)，其中短链PHA的单体碳链长度一般为3–5，而中长链PHA的单体碳链长度在6–14之间。一般来说，天然微生物只能积累SCL PHA或MCL PHA中的一类。

根据组成单体种类的多少，PHA可以分为均聚物(Homopolymer) 和共聚物(Copolymer)，后者可进一步细分为随机共聚物(Random copolymer) 和嵌段共聚物(Block copolymer)。

此外，由于PHA单体的侧链R基团十分多样，理论上可以引入具有双键或三键、卤素、氨基、苯环等功能基团的单体[9-10]，而这些基团又允许通过后期无限可能性的化学修饰增加新的官能团，形成所谓的“功能PHA”。功能PHA能够改善材料性能，并带来诸如温敏、光敏、pH值调节等特殊材料功能[11-14]。

因此，取决于PHA的单体种类及比例、聚合形式、侧链基团、分子量等，形成了丰富的PHA结构，由此带来了材料性能上的多样性，包括PHA热力学性能、生物相容性和生物可降解性及其他性能，拥有广阔的应用前景。

PHA的结构通式、多样性示意见图 1。

图 1 PHA结构通式及多样性

Fig. 1 General molecular formula and PHA diversity.

图选项

1.2 PHA的生物合成途径微生物合成的PHA在很大程度上依赖于所供给的碳源，简单地说，这些碳源可以分为相关碳源和非相关碳源两类。PHA生物合成过程中有多条代谢途径能够合成羟基脂酰辅酶A单体，这些途径又与体内的中心代谢途径相耦联，形成一个巨大的代谢网络。不同细菌利用的碳源不同，所使用的PHA合成途径不同，合成PHA的种类也不同，这种差异与特定微生物中起作用的代谢途径有关。

目前，在自然条件下细菌中已经报道的PHA单体的合成途径一共有14种[9]。其中，最常见也是代谢工程改造研究最为成熟的，是与SCL PHA合成相关的乙酰辅酶A直接合成PHB途径，以及与MCL PHA合成相关的β氧化循环途径和脂肪酸从头合成途径(图 2)。

图 2 PHA的主要生物合成途径[6, 15-17] (PhaA：β-酮基硫解酶(β-ketothiolase)；PhaB：NADPH/NADH依赖型乙酰乙酰辅酶A还原酶(NADPH/NADH-dependent acetoacetyl-CoA reductase)：PhaC：PHA聚合酶(PHA synthase)；PhaG：3-羟基脂酰-ACP: CoA酰基转移酶(3-hydroxyacyl-ACP: CoA transacylase)；PhaJ：(R)-烯脂酰辅酶A水合酶[(R)-enoyl-CoA hydratase]；FabG：3-酮脂酰-ACP还原酶(3-ketoacyl-ACP reductase))

Fig. 2 Main PHA biosynthetic pathways[6, 15-17].

图选项

2 代谢工程技术在PHA生产中的应用

2.1 生物代谢通路的基因编辑工具精确的基因编辑技术使研究者可以根据需求对基因特定位点进行改造，从而在基因水平上对代谢通路进行调节。20世纪90年代，研究人员将可以特异性识别三联碱基对的锌指蛋白与核酸酶FokⅠ进行偶联，开发出了锌指蛋白核酸酶技术(Zinc finger nucleases，ZFNs)。但因其识别的DNA序列数量有限，很大程度上也被限制了应用[18-19]。随后，根据改造的黄单胞菌属的TAL蛋白可以特异性识别DNA中一个碱基的特点，研究人员又开发出了类转录激活因子效应物核酸酶技术(Transcription activator-like effector nucleases，TALENs)。此技术理论上可以对任意基因序列进行编辑，但因其操作较为烦琐，应用同样受到了限制[19-20]。近年来，随着成簇规律间隔短回文重复序列/成簇规律间隔短回文重复序列关联蛋白(Clustered regulatory interspaced short palindromic repeats/CRISPR-associated protein，CRISPR/Cas)的发现，基因编辑技术有了重要突破[21-22]。CRISPR/Ca是细菌和古菌中普遍存在的天然免疫系统，研究人员对其加以利用，开发出新一代基因编辑技术CRISPR/Cas9，可对靶向基因位点进行剪切[23-24]。与之前的技术相比，CRISPR/Cas9更加灵活、高效、廉价且操作简便。基于CRISPR/Cas9开发出的CRISPRi (CRISPR interference) 和CRISPRa (CRISPR activation) 技术可以在不改变DNA的情况下可逆地抑制或上调基因表达，大大扩展了CRISPR/Cas9工具箱[25-26]。

将各种技术结合使用可以满足多种基因调节需求，为研究带来极大的便利。这些基因编辑工具已经在调节PHA相关代谢通路、导入外源代谢途径、改变细胞形态等各方面发挥出巨大的作用，为增强PHA生产助力[27]。

2.2 代谢工程增强PHA生产

2.2.1 代谢流调控增加PHA产量在生物获取的物质和能量一定的情况下，将这些物质和能量更多地引向PHA相关通路，理论上可以积累更多的PHA。在PHA发现之初，研究者就通过控制培养条件对PHA的合成、降解等特性进行研究，以求得到更高的产率[28-31]。而后通过提供不同的前体在多种细菌中发现了不同种类的PHA[32]。直到1989年在罗氏真氧菌Ralstonia eutropha中首次鉴定了PHA生物合成操纵子phaCAB，自此开始了针对phaCAB等PHA合成相关基因的调控[33-34]。

PHA合成相关基因稳定的强表达对于把底物引向PHA合成方向、提高底物转化率从而增加PHA积累是至关重要的，其中又以PHA聚合酶PhaC最为关键。PhaC决定着合成的PHA的诸多特性，包括产率、单体类型和组成、分子量及多分散性[35]。为增强PhaC的活性和改变底物特异性，研究人员已经在PhaC的编辑上进行了很多研究。在近年PhaC的晶体结构被解析之前[36-38]，编辑PhaC的方法主要依赖于随机诱变和筛选以及基于序列同源性的结构预测[39-41]。例如，通过对假单胞菌Pseudomonas sp. 61-3的随机诱变和筛选，研究者发现Glu130、Ser325、Ser477和Gln481是决定PhaC底物特异性和活性的重要残基。与野生型相比，Glu130Asp、Ser325Thr、Ser477Gly和Gln481Lys的突变体有更强的聚合活性，可以使PHB产量增加400倍[42-44]。

之后又开发出了很多方法调控PHA合成相关基因的表达。比如将大肠杆菌Escherichia coli JM109基因组上phaCAB的拷贝数从11增加至50，可以使PHB积累量从0.1 g/L增加至1.30 g/L。这项实验结果表明，更高的PHA合成基因拷贝数可带来更高的PHA产量[45]。此外还可以用强诱导转录系统过表达PHA合成基因，研究人员开发了一种由噬菌体聚合酶衍生的类T7诱导系统，实验表明该系统在诱导后有较强的转录活性[46]。在盐单胞菌Halomonas bluephagenesis的基因组上整合该类T7启动子驱动的phaCAB基因，诱导44 h后，PHA产量达到了69 g/L，而同样条件下野生型只积累了50 g/L PHA。

插入或删除基因也是一种增强PHA生产的常用策略，但是这种方法往往只注重局部的通路设计而忽略对细胞生长产生的不利影响。在现代计算机技术的帮助下，结合代谢流建模对细菌生产途径进行电脑模拟有助于设计和优化通路以达到最优的产品生产[47]。例如，现在已经建立了恶臭假单胞菌Pseudomonas putida代谢流的电脑模拟模型，用于预测底物向PHA合成酶及前体转化的最佳流量。初步的模拟分析显示，敲除葡萄糖脱氢酶(Gcd) 的菌株与野生型相比，PHA积累量可增加100%。在实验中，敲除Gcd的P. putida表现出了更高的PHA产量(+80%) 和胞内PHA含量(+50%)，同时生成的副产物也更少，而且细菌生长几乎没有受到影响。这样构建的重组菌在所有工业生产相关评价标准下都是最优的[48]。同样地，根据初步模型预测，P. putida KT2440中过表达丙酮酸脱氢酶亚基(AcoA) 的同时敲除Gcd可以使PHA产量增加120%，实际实验中PHA产量增加了121%[47]。

2.2.2 构建重组通路利用廉价原料生产PHA 得益于近几十年来在生物化学和分子生物学领域对PHA生物合成愈加透彻的理解，以及对许多细菌中PHA合成基因的成功克隆，多种细菌通过代谢工程改造成为了高性价比的PHA生产平台。其中最具有代表性的例子就是带有来源于R. eutropha的phaCAB操纵子的E. coli，这种改良的E. coli拥有能与原始R. eutropha相媲美的高PHB产量和产率[49-51]。通过导入适合的PhaC，E. coli、R. eutropha、Pseudomonas sp.等菌种还可被用来更高效地生产SCL-co-MCL PHA[52-55]。除细菌外，酵母和一些植物也被成功改造，可进行PHA生产[56-57]。

同时构建重组代谢通路避免使用昂贵的相关碳源也是利用代谢工程降低PHA生产成本的重要思路。例如，最初聚3-羟基丁酸-3-羟基戊酸(PHBV) 生产需要添加丙酸或戊酸钠生成3HV的中间体丙酰辅酶A[58-59]，为了避免使用这些高价格的前体，研究人员构建了通过α-酮丁酸和甲基丙二酰辅酶A生产丙酰辅酶A的通路，以用更廉价的非相关碳源生产PHBV[60-62]。类似地，生产聚3-羟基丁酸-4-羟基丁酸(P34HB) 通常需要使用γ-丁内酯或丁酸[59, 63]，作为更经济的选择，可以利用克氏梭菌Clostridium kluyveri的琥珀酸半醛脱氢酶(SucD) 和4HB脱氢酶(4HbD) 从葡萄糖生产4HB[64-65]。通过导入编码β-呋喃果糖苷酶的sacC基因，可在R. eutropha NCIMB11599和R. eutropha 437-540中构建蔗糖利用通路。β-呋喃果糖苷酶被分泌到培养基中，将蔗糖水解为葡萄糖和果糖以供细胞生长。在含20 g/L蔗糖的无氮培养基中生长的R. eutropha NCIMB11599可获得占细胞干重73%的PHB[66]。

此外还有许多利用菌种独特代谢通路使用各种廉价原料进行PHA生产以求降低成本的研究，比如蔗糖蜜、木薯和玉米淀粉、木质纤维素水解物、乳清以及废弃物中提取的碳源等[59, 67-71]。近年来也出现了很多针对利用气体碳源如CO、CO2、CH4等生产PHA的研究，例如甲烷氧化菌Methylosinus trichosporium、R. eutropha、聚球菌Synechococcus sp. 等一系列天然PHA生产菌都有以气体一碳底物作为碳源生产PHA的能力[72-74]。

2.2.3 改造β氧化途径利用脂肪酸高效合成不同链长PHA β氧化途径是PHA合成的3条主要途径之一，选用脂肪酸作为底物来提供短链和中长链单体生产PHA是经常采取的方法[75-79]，对β氧化途径进行改造对于促进MCL PHA或短中长链共聚PHA (SCL-co-MCL PHA) 的合成具有重要意义。在1994年首次报道了豚鼠气单胞菌Aeromonas caviae能利用烷酸和油生产聚3-羟基丁酸-3-羟基己酸(PHBHHx) 的随机共聚物[80]。β氧化是这个过程中的主要通路，脂酰辅酶A脱氢酶(FadE) 催化脂酰辅酶A生成烯酰辅酶A的反应是β氧化过程中的限速步骤。有研究表明，在E. coli中过表达FadE可以使烯酰辅酶A的量增多，再表达PhaJ和PhaC可以使重组菌积累更多的PHA[81]。

然而在β氧化过程中细胞可能会将大部分脂肪酸转化为乙酰辅酶A用于细胞生长，从而将昂贵的脂肪酸浪费在能用葡萄糖等廉价底物生产的乙酰辅酶A上[64-65, 82]。因为β氧化的存在，脂肪酸转化为PHA的效率低，导致MCL PHA生产成本升高。因此，改造β氧化途径也是提高PHA生产效率的一种可行策略。

敲除P. putida或嗜虫假单胞菌Pseudomonas entomophila内β氧化途径中3-羟基脂酰辅酶A脱氢酶(FadB) 及3-酮脂酰辅酶A硫解酶(FadA)可以使大多数脂肪酸转变成3-羟基脂酰辅酶A用于合成PHA，而不是被氧化成乙酰辅酶A，从而显著提高底物到MCL PHA的转化率[82-85]。据报道，部分敲除β氧化途径或者利用丙烯酸抑制β氧化可以获得与底物添加脂肪酸链长相同或更长的单体，底物中各种脂肪酸的比例还可以影响PHA的组成成分[85-86]。部分敲除β氧化的P. putida KT2442可作为可控的PHA生产平台，通过添加预定比例的脂肪酸精确调节PHA的单体比例，并以此合成了随机和嵌段共聚物聚3-羟基丁酸-3-羟基己酸[P(3HB-co-3HHx)]，单体组成和材料性能稳定[87-88]。类似地，通过部分敲除β氧化途径和导入乙酰辅酶A直接合成PHB途径，重组P. entomophila LAC32被成功开发成SCL-co-MCL PHA的合成平台，并合成了聚3-羟基丁酸-3-羟基癸酸[P(3HB-co-3HD)]、聚3-羟基丁酸-3-羟基十二酸[P(3HB-co-3HDD)] 等多种新型PHA[89]。Pseudomonas spp.脂肪酸氧化突变体还可以生成包含3-羟基己酸(3HHx)、3-羟基辛酸(3HO)、3-羟基癸酸(3HD) 和3-羟基十二酸(3HDD) 的均聚、无规共聚或嵌段共聚的中链PHA[10]。但值得注意的是，只使用脂肪酸培养的β氧化缺陷菌可能会生长缓慢或只积累少量的MCL PHA[86, 90-91]。

2.2.4 设计引入新通路生产非天然PHA 以各种经过充分研究的通路作为基础，可以从目的产物出发设计构建新的生产通路。例如，乳酸和乙醇酸的共聚物(PLGA) 是一种应用广泛的可生物降解、高生物相容性的医用聚合物。在导入了新月柄杆菌Caulobacter crescentus的Dahms途径并敲除了磷酸烯醇式丙酮酸-糖磷酸转移酶系统中葡萄糖转运体亚基(PtsG) 后，重组E. coli可以以木糖为原料生产乙醇酸。这种E. coli可以同时利用葡萄糖生产乳酸并用木糖生产乙醇酸。之后用一种进化的丙酰辅酶A转移酶将乳酸和乙醇酸在体内转化为CoA中间体。最后利用进化的PHA聚合酶将这些CoA中间体聚合成PLGA[92]。如图 4所示，用相似的方法还合成了聚2-羟基丁酸-3-羟基丁酸、聚乳酸-羟基乙酸-3-羟基丁酸-4-羟基丁酸等多种聚合物，以及一些芳香族聚酯[93-97]。通过编辑L-苯丙氨酸生物合成途径，可以使E. coli利用葡萄糖有效生产含苯乳酸(PhLA) 的聚合物。在这条通路中，磷酸烯醇式丙酮酸(PEP) 和赤藓糖-4-磷酸(E4P) 依次转化为3-脱氧-D-阿拉伯庚酮糖酸-7-磷酸(DAHP)、预苯酸、苯丙酮酸、PhLA、PhLA-CoA[97-98]；同时构建了由L-苯丙氨酸合成肉桂酰辅酶A的通路，作为辅酶A的供体[97]。

图 3 敲除部分β氧化以增强PHA生产[82](Acyl-CoA：脂酰辅酶A；Enoyl-CoA：烯酰辅酶A；(S)-3- hydroxyacyl-CoA：(S)-3-羟基脂酰辅酶A；3-ketoacyl- CoA：3-酮脂酰辅酶A；(R)-3-hydroxyacyl-CoA：(R)-3-羟基脂酰辅酶A)

Fig. 3 Deleting β-oxidation related genes for enhanced PHA production[82].

图选项

图 4 引入新通路构建多种单体PHA生产途径[93-96]((R)-citramalate：(R)-柠苹酸；2-ketobutyrate：2-酮丁酸；2-hydroxybutyrate-CoA：2-羟基丁酰辅酶A；3-hydroxybutyrate-CoA：3-羟基丁酰辅酶A；Citrate：柠檬酸；Succinyl-CoA：琥珀酰辅酶A；Succinate：琥珀酸；4-hydroxybutyrate-CoA：4-羟基丁酰辅酶A；Lactate：乳酸；Lactyl-CoA：乳酰辅酶A；Xylose：木糖；Xylonolactone：木糖酸内酯；Xylonate：木糖酸；2-keto-3-deoxy-xylonate：2-酮基-3-脱氧木糖酸；Glycolaldehyde：乙醇醛；Glycolate：乙醇酸；Glycolyl-CoA：羟乙酰辅酶A)

Fig. 4 Introducing new pathways to produce PHA with various monomers[93-96].

图选项

3 PHA的低成本生产经过近30年的产业化探索，PHA的大规模应用仍然面临困难。相较于传统石油基塑料制品，PHA严重受制于它高昂的生产成本。为降低PHA的生产成本，从而提升其在材料市场上的竞争力，近年来，研究人员在运用代谢工程技术改造PHA生产菌株以简化下游加工过程上取得了一些新进展。

3.1 形态学工程工业生物技术通常涉及在大型发酵罐中进行微生物发酵，然后进行下游加工处理，即从发酵培养液中分离出微生物生物质，再分离提取胞内产物或上清液产物。而实现分离通常需要昂贵且耗能大的连续离心、微过滤或费时的重力沉淀等。

PHA的生产成本高昂的一个重要因素就是细菌细胞及胞内产物PHA的下游加工过程花费较高。由于大多数菌株细胞的大小在0.5–2.0 μm之间，较小的细胞不仅增加了细菌生物量与培养液的分离难度，同时也限制了每个细胞中PHA颗粒的储存量。通过形态学工程改造PHA生产菌株，有助于提供更大的细胞空间来积累PHA颗粒；还有助于加速细胞沉淀，使细菌细胞易于通过重力与培养液分离，从而有效降低PHA的生产成本[99-101]。

细胞的形态受许多基因调控影响，包括细胞壁装配相关基因mreB (编码细胞骨架肌动蛋白MreB)、mreC (编码杆状细胞形状决定蛋白MreC)、mreD (编码杆状细胞形状决定蛋白MreD)、rodZ (编码细胞骨架蛋白RodZ)、rodA (编码杆状细胞形状决定蛋白RodA)、pbp2 (编码青霉素结合蛋白PBP2)、pbp3 (编码青霉素结合蛋白PBP3)、细胞分裂相关基因ftsZ (编码细胞分裂蛋白FtsZ)、ftsA (编码细胞分裂蛋白FtsA)、sulA (编码细胞分裂抑制蛋白SulA)、minC (编码Z环定位蛋白MinC) 和minD (编码Z环定位蛋白MinD)等[102]。在这些基因中，已在大肠杆菌或嗜盐菌中成功操作mreB、ftsZ、sulA、minC和minD基因来改造细胞形态，简化下游生物加工过程。

SulA是一种细胞分离抑制蛋白，当与细胞分裂的Z环相互作用时，SulA的过表达会阻止细胞分裂，从而将正常的杆状大肠杆菌转变成丝状细胞[103]。丝状化增加了细胞体积，为PHA颗粒的积累提供了更多空间(图 5)。相比于野生型E. coli，过表达SulA抑制Z环形成的丝状细胞能够比野生型多储存27%的PHB[101]。

图 5 过表达SulA/MinCD导致细胞丝状生长[102]

Fig. 5 Overexpression of SulA/MinCD leads to ﬁlamentary growth[102].

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MreB是一种细菌细胞骨架肌动蛋白，用以维持许多细菌的杆状形态[104]，也被认为是用于扩大细胞体积的合适靶标。当在mreB缺失突变体中回补表达mreB后，细胞形态变为更大的球形，并且观测到在重组大肠杆菌中PHB的积累量可增加100%以上[99]。

由MinD募集到细胞极的MinC是与FtsZ相互作用以抑制Z环组装的蛋白质[105]。类似于SulA诱导大肠杆菌丝状细胞的形成，在H. bluephagenesis TD08的生长静止期中，过表达MinCD抑制剂可诱导产生丝状细胞(图 5)，使PHA含量从69%增至82%[106]。并且观测到细胞形成了数百微米的相互缠绕的纤维网络，其中较短的细胞在重力作用下一起包装和沉淀，与正常的离心分离相比，可以更轻松地将细胞从培养液中分离出来，这大大简化了生物质的下游加工过程[106]。此外，当MinCD在敲除了PHA颗粒相关蛋白(PhaP) 的H. bluephagenesis菌株中过表达时，观测到最大可积累的PHA颗粒大小达10 μm[100]。

3.2 自絮凝生物自絮凝是指某些微生物自发展现出受控聚集的能力，形成大量且高度致密的细胞絮凝物，从而降低从培养基中回收生物质的难度，有利于实现简单经济的下游处理[107-108]。例如，当删除了盐单胞菌Halomonas campaniensis LS21编码电子转移链中两个电子转移黄素蛋白亚基的etf操纵子后，细胞表面电荷减少和细胞疏水性增加，细胞趋于自絮凝；在停止搅拌和通气后，大多数细胞迅速絮凝并沉淀至生物反应器的底部，整个过程持续不到1 min且没有能量消耗，从而减少了下游分离的能量消耗[109]。此外，自絮凝还拥有诸如发酵培养基循环再使用等其他优点。收集完沉淀的细胞团后，无需灭菌或接种，培养基上清液即可再次使用；无废水发酵工艺可以至少循环运行4次而不产生废水[109]。

4 下一代工业生物技术(Next generation industrial biotechnology，NGIB)

4.1 现代工业生物技术面临的问题随着分子生物学、生物化学和合成生物学的快速发展，工业生物技术已经发展成为生产化学品和材料更有效的手段。然而，与化学工业相比，目前的工业生物技术在生产化学品、材料和生物燃料等方面仍然存在生产成本较高、竞争力不足的问题。工业生物技术需要通过微生物的大规模发酵培养生产产品，因此在发酵过程中，如何廉价高效地避免杂菌污染是长久以来人们关注的重点。发酵过程中一旦沾染了杂菌，轻则降低物料利用率和产物收率，严重时则必须从头开始生产流程，带来极大的经济损失。在生产前对发酵设备进行灭菌处理是现在普遍采取的方法，然而这些方法也带来了不可忽视的高能耗成本，同时依然无法完全规避杂菌污染风险。因此必须进一步发展“下一代工业生物技术”，以更少的淡水消耗、节能和持久的开放式发酵为基础，克服目前工业生物技术的缺点，将目前的工业生物技术转化为具有竞争力的工艺。其中，以抗污染的极端微生物作为代谢改造及发酵培养的底盘菌株将会是NGIB成功的关键。

表 1 近30年来代谢工程在PHA微生物合成中的主要研究进展

Table 1 Advances in metabolic engineering of PHA microorganism biosynthesis in recent 30 years

Years

Types

Manipulations

Effects

Microorganisms

References

1988

Constructing recombinant pathways

+phaCAB operon from R. eutropha

Producing PHA in E. coli

E. coli

[50]

1997

+sucD and 4hbD from Clostridium kluyveri

Producing P34HB from glucose

E. coli

[64]

2002

+Acinetobacter phaBCA and E. coli sbm and ygfG, ΔprpC

Producing PHBV with significant HV incorporation from glycerol

Salmonella enterica

[60]

2014

+E. coli poxB L253F V380A, R. eutropha prpE, phaCABRe, ΔprpC ΔscpC

Producing P(3HB-co-5.5 mol% 3HV) from glucose

E. coli

[61]

2014

Introducing sacC to construct sucrose utilization pathway

Producing 73 wt% PHB from nitrogen free medium containing 20 g/L sucrose

R. eutropha

[66]

2004

Flux tuning for higher PHA accumulation

+phaABRe, phaJ4Pa, position 325 and 481 mutated PhaC1Ps

Accumulated more P(3HB-co-3HA)

E. coli

[42]

2005

+phbABRe, phaJ4Pa, phaC1Ps E130D

Accumulating 10-fold higher PHB from glucose; producing more P(3HB-co-3HA) copolymer grown on dodecanoate

E. coli

[43]

2006

+phaABRe, phaJ4Pa, phaC1Ps S477R

Shifting in substrate specificity to smaller monomers containing a 3HB unit

E. coli

[44]

2014

Pathway design guided by modeling simulation

An increase of 121% PHA accumulation

P. putida

[47]

2015

Increasing the copy number of phaCAB

Enhancing PHB accumulation from 0.1 g/L to 1.30 g/L

E. coli

[45]

2017

Overexpressing phaCAB by T7-like promoter

Enhancing PHB accumulation from 50 g/L to 69 g/L

H. bluephagenesis

[46]

1998

Modification of β-oxidation pathway

+phaC1 from P. aeruginosa in fadR deletion mutant, adding acrylic acid

Accumulating 60 wt% PHA from decanoate

E. coli

[86]

2009

ΔfadBA

Producing PHA with 71 wt% P3HHp from heptanoate

P. putida

[83]

2010

+fadE and phaC

Improved PHA production

E. coli

[81]

2010

ΔfadBA ΔfadB2x ΔfadAx ΔPP2047 ΔPP2048 ΔphaG

Producing PHD or P(3HB-co-84 mol% 3HDD) from decanoic acid or dodecanoic acid

P. putida

[85]

2011

ΔfadBA ΔPSEEN 0664 ΔPSEEN 2543

Producing 90 wt% PHA with 99 mol% 3HDD

P. entomophila

[82]

2018

ΔfadBA ΔPSEEN 0664 ΔPSEEN 4635 ΔPSEEN 4636 ΔphaG ΔphaC1-phaZ-phaC2

Producing novel SCL-co-MCL PHA including P(3HB-co-3HD), P(3HB-co-3HDD) and P(3HB-co-3H9D)

P. entomophila

[89]

2012

Producing non-natural polyesters

ΔldhA, +phaC1437, pct540, cimA3.7, leuBCD, panE from Lactococcus lactis Il1403 and phaAB from R. eutropha

Producing P(2HB-co-3HB-co-LA) with small amounts of 2HB and LA monomers from glucose

E. coli

[93]

2016

Introducing Dahms pathway in ptsG deletion mutant

Producing PLGA from glucose and xylose

E. coli

[92]

2016

+ilvBNmut, ilvCD, panE, pct540 and phaC1437

Producing PHA containing 2-hydroxyisovalerate

E. coli

[94]

2017

Δsad ΔgabD ΔglcD, +p68pcH5Z and pMCS-ycdW-aceAK

Producing P(GA-co-LA-co-3HB-co-4HB) from glucose

E. coli

[96]

2018

Manipulating L-phenylalanine biosynthesis pathway

Producing PhLA-containing polyesters

E. coli

[97-98]

1993

Morphology engineering

+ftsZ

Accelerating cell division, high cell density with 127 g/L PHB

E. coli

[103]

2014

+sulA

Filamentary cells, PHB storage increased by 27% compared to wild type

E. coli

[101]

2014

+minCD

Filamentary cells, enhancing PHA content from 69% to 82%

H. bluephagenesis

[106]

2015

+mreB in mreB deletion mutant

Larger spherical cells, an increase of over 100% PHB accumulation

E. coli

[99]

2019

+minCD in phaP deletion mutant

Accumulating PHA granules up to 10 μm

H. bluephagenesis

[100]

2018

Self-flocculation

Δetf

Most cells rapidly flocculate and precipitate to the bottom in less than 1 min

H. bluephagenesis

[109]

表选项

4.2 基于极端微生物的NGIB及其优势极端微生物可以在大多数微生物都无法增殖的苛刻条件下(诸如极端pH、极端温度或高渗透压) 生长，正因如此，它们在发酵过程中对杂菌有更强的抵抗能力。选择在极端条件下生长良好的稳健菌株作为底盘菌，并通过代谢工程导入新的通路或添加新的基因元件，可以使这种能力进一步增强，使其适合开放连续式的大规模发酵生产。

以PHA生产为例，结合多种生物工程技术，可以将极端微生物开发成优秀的PHA生产底盘菌，这不仅将简化生产流程也会显著降低PHA生产成本。嗜盐单胞菌H. bluephagenesis和H. campaniensis就是其中两个很好的例子，其能够在高盐浓度、高pH条件下快速生长，使得它们拥有其他微生物难能媲美的抗污染能力。据报道嗜盐菌在未经灭菌的海水培养基中可以持续开放发酵至少两个月而不被杂菌污染[110]。野生型H. bluephagenesis能在pH 8.0–9.0含有60 g/L NaCl的葡萄糖培养基中快速生长并积累高达细胞干重80%以上的PHA[111]。极端嗜盐古菌Natrinema ajinwuensis RM-G10也能在pH 7.0的200 g/L NaCl组成的高盐培养基中积累60%以上的PHA[112]。除嗜盐菌外，嗜热菌也被用作生产PHA的经济宿主。例如，嗜热的沙氏芽孢杆菌Bacillus shackletonii K5菌株可以在45 ℃和pH 7.0条件下合成高达其细胞干重73% (9.76 g/L) 的PHB[113]。

4.3 对基于极端微生物的NGIB进行的代谢改造下面将以H. bluephagenesis为例，分享改造NGIB菌株的经验，希望能起到抛砖引玉的作用。

从新疆艾丁湖分离出的中度嗜盐菌H. bluephagenesis可以在高盐浓度、高pH的含葡萄糖矿质培养基中快速生长并能利用多种碳源积累丰富的PHB。Zhao等在H. bluephagenesis基因组上整合了类T7表达系统调控phaCAB基因，显著增强了phaCAB的转录，提高了PHB产量[46]。Qin等在H. bluephagenesis中构建及优化了CRISPR/Cas9和CRISPRi系统，为高效基因组编辑奠定了基础[114]。Ling等通过阻断电子传递途径改变了H. bluephagenesis中NADH和NAD+的比例，增加了PHB的积累[115]。此外H. bluephagenesis还被改造为能生产P34HB、PHBV等PHA的底盘菌，Ye等在H. bluephagenesis中构建两条4HB合成途径的同时敲除了与4HB竞争的琥珀酸半醛脱氢酶，以葡萄糖为单一碳源在7 L发酵罐中非无菌开放发酵60 h得到了干重26.3 g/L的菌体和占干重的60.5%的P34HB，其中4HB摩尔比为17.04%[116]。尹进等插入甲基丙二酰辅酶A变位酶和脱羧酶(ScpAB)，并敲除了2-甲基柠檬酸合成酶(PrpC) 后获得了能以葡萄糖为单一碳源稳定生产3HV含量为5–12 mol%的PHBV的菌株[45]。

4.4 NGIB面对的挑战尽管嗜盐菌已被设计成为PHA生产菌，其依然存在一些有待解决的问题，比如高盐造成的钢制设备锈蚀、诱导系统成本高、高盐废水处理和基因操作不便等问题[117-118]。借助合成生物学和代谢工程技术，部分阻碍嗜盐菌进一步工业开发的问题得到了一定的缓解，比如H. bluephagenesis适应高pH环境(pH > 8.5)，而在这样的碱性条件下钢制品耐锈蚀能力较强；多种诱导体系也逐步引入菌株中以实现用温度、光线、pH或溶氧等方法实现低成本诱导[119-122]。相信在未来会有更多问题得到解决，使NGIB得到更广泛的应用。

5 总结与展望 PHA因其具有良好的生物可降解性和生物相容性，以及种类和性能的多样性，受到广泛关注。随着越来越多的新型功能PHA被开发出来，PHA的应用面将进一步扩大。然而生产成本和热力学性能依然是制约PHA大规模生产和商业化的最大难题。

通过合成与系统生物学、代谢工程、下一代生物工业技术等手段，以极端微生物作为PHA的低成本生产平台菌株，可通过无需灭菌的开放式连续发酵，大大简化生物制造过程。同时，利用代谢工程和合成生物学技术对生产菌株进行改造，使更多的代谢流转向PHA合成，可以提高底物转向PHA的转化率；对菌株进行形态学、自絮凝改造，可以简化PHA下游提纯加工流程，从而大幅度降低PHA的生产成本。另一方面，还需要不断开发能够改善PHA性能的新单体(及最优的单体比例)、新结构和加工工艺等，使PHA热力学性能可以接近甚至超越石油基塑料，进一步促进PHA的应用与推广。

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PHB化学降解方法？ - 知乎

PHB化学降解方法？ - 知乎首页知乎知学堂发现等你来答切换模式登录/注册化学化学实验PHB化学降解方法？PHB（聚 [公式] -羟基丁酸酯）作为一种新型材料具有良好的生物降解特性，应用前景广阔，在化学降解方面有何研究进展显示全部关注者5被浏览1,969关注问题写回答邀请回答好问题添加评论分享3 个回答默认排序yjjart有机化学等 2 个话题下的优秀答主关注谢邀。从结构上来看，用氢氧化钠溶液就可以实现化学降解。发布于 2014-04-09 23:49赞同 3添加评论分享收藏喜欢收起裂章有机光电phD，固体电子学关注其实一般说来，容易降解主要指结构中存在薄弱位置，容易遭到破坏。比如双键，酯基，肽键等。由于存在这些容易发生化学反应的部位，高分子可以降解成低聚物或者小分子，但一般不会直接变成单体。化工上面可以利用逆反应和化学平衡来回收单体，比如水解、醇解。

上面主要讲的是聚合物是一次结构，它们的影响最大。另外二次结构和凝聚态结构也有影响，比如分子量和结晶度。

PS：有一篇关于利用DNA编码合成来改性纤维素的报道，利用的就是在纤维素结构中引入酯基，从而使纤维素降解和预处理变得容易。发布于 2014-04-10 11:34赞同 1添加评论分享收藏喜欢收起写回答1 个回答被折叠（为什

PHB（PHB服务）_百度百科

PHB服务）_百度百科网页新闻贴吧知道网盘图片视频地图文库资讯采购百科百度首页登录注册进入词条全站搜索帮助首页秒懂百科特色百科知识专题加入百科百科团队权威合作下载百科APP个人中心PHB是一个多义词，请在下列义项上选择浏览（共2个义项）添加义项收藏查看我的收藏0有用+10PHB播报讨论上传视频PHB服务PHB，是指为满足移动网络上多种业务对QoS的需求，IETF先后制订的两种服务模型：集成服务模型和区分服务模型。集成服务模型分为保障型业务和控制负载业务两种服务类型。中文名PHB服务外文名Service PHB服务模型集成服务模型和区分服务模型业务分类保障型业务和控制负载业务目录1简介2分类简介播报编辑Service PHB，PHB服务区分服务模型则简化了信令，对业务流的分类粒度更粗。它采用汇聚和PHB(Per Hop Behavior)的方式来提供一定程度上的QoS保证。汇聚的含义在于路由器可以把QoS需求相似的业务流看成一个类，以减少调度算法处理的队列数量；而PHB的含义在于逐级跳的转发方式，每个PHB对应一种转发方式或QoS要求。区分服务通过设置数据包头中的保证比特位将数据包分为奖赏数据包和尽力而为数据包。当这些数据包到达路由器时，它们能够向路由器表明自己的身份，从而得到不同的处理。区分服务（DiffServ）是IETF工作组为了克服IntServ的可扩展性差而提出的另一个服务模型，目的是制定一个可扩展性相对较强的方法来保证IP的服务质量(QoS)。与DiffServ有关的因特网草案（Internet-Drafts）有：An Informal Management Model for Diffserv RoutersManagement Information Base for the Differentiated Services ArchitectureNew Terminology and Clarification for DiffservDifferentiated Services Quality of Service Policy Information BaseAn Assured Rate Per-Domain Behaviour for Differentiated Services与DiffServ有关的RFC（Request For Comments）有：Definition of the Differentiated Services Field (DS Field) in the IPv4 and IPv6 Headers (RFC 2474)　AnArchitecture for Differentiated Services (RFC 2475)Assured Forwarding PHB Group (RFC 2597)Differentiated Services and Tunnels (RFC 2983)Definition of Differentiated Services Per Domain Behaviors and Rules for their Specification (RFC 3086)　Per Hop Behavior Identification Codes (RFC 3140)An Expedited Forwarding PHB (RFC 3246)Supplemental Information for the New Definition of the EF PHB (RFC 3247)A Delay Bound alternative revision of RFC2598 (RFC 3248)当数据流由客户进入DiffServ域(如域A)时，边缘路由器通过标识该字段，将IP包首先分为不同的服务类别，而网络中的其他传送转发路由器在收到该IP包时，则根据该字段所标识的服务类别将其放入不同的队列，并且由作用于输出队列的流量管理机制控制每一个队列，即给予不同的每一跳行为(PHB)。其中最主要的就是对每个队列给出带宽分配，以及发生阻塞时如何丢包，这些资源的分配规则都是预先设定好的。分类播报编辑在DiffServ域中，路由器大致可以分为两类：1、边缘路由器；2、传送路由器(核心路由播)。其中传送路由器只负责将进入的数据包按级别排队，并按事先设定的带宽、缓冲处理输出队列。　边缘路由器除了完成上述功能以外，还在输入接口处设有检查机制以监视用户是否遵守业务等级协定(SLP)，分类机制以标识输人的每个业务包，并将其分别排入相应的队列。DiffServ的设计思想是希望使用一种与目前lP网络协议相结合的方式来实现对网络QoS的保证，因此其实现要比使用端到端控制的IntServ简单，网络额外负担也较小。现在IETFRSVP和DiffServ两个工作组都正在研究RSVP与DiffServ相结合的问题，以进一步扩大DiffServ与现有系统的可兼容性。DiffServ模型本身也还不完善。首先它并不提供全网端到端的服务质量保证，尚需进一步明确和开展的研究包括：(1) 业务分类的具体划分实现；(2)每个业务性能的量化描述；(3)IP的业务类型与ATM QoS的映射等。以上所有文件还未形成真正的标准（即RFC文档）。要实现对IP网络的QoS保证尚处于研究和实验阶段。国内外都对它抱有很大的希望，美国100多所大学参加的Internet2工程已经把DiffServ模型推向QoS测试网，一般称为QBone，可望不久的将来能展示出一个全新的网络。区分服务在实现上由每跳行为（PHB，Per Hop Behavior）、包的分类机制和流量控制功能(测量、标记、整形、策略控制)三个功能模块组成。区分服务实现可扩展性的重要策略是在网络中心节点只进行转发操作，将分类和大部分流控的复杂性操作转移到了网络边缘节点。同时，将同类的流聚集传输，避免了大量的流状态信息的保存，大大降低了网络实现的复杂性和网络负荷。区分服务的基本思想是在网络边缘将进入的流分成各种不同的类型，将同种类型的流合并起来进行集束传输，并对每一种类型在网络中分别进行处理。分类的工作在网络的入口处进行，分类通过检查包的一个或多个字段的内容来完成。包被标识为一定的服务类型，并记录在包头字段里，随后将包按一定的流量控制策略送入网络。网络中转发包的核心路由器通过检查包头来确定对包进行何种处理。每种服务类型都要给予不同的处理方式，以获得相应的服务质量。核心路由器对包所做的处理包括将包置入哪一种队列，网络拥塞时以何种丢包策略对包进行丢弃等。区分服务中传输的是流聚集而不是单个的流，每一组流聚集都具有相应的各自不同的流传输服务标准，在各个域内部根据不同的媒体传输要求提供不同的传输服务。这一过程是通过区分服务中IP包头的区分服务标记字段(DS Field)来实现的，DS的标记字段在IPv4中定义在包头的TOS字节，在扩展的IPv6中定义在包头的流类型字节（Traffic Class Octet）的前六位。DS标记字段对应相应传输媒体的PHB。传输分类的过程是在边界节点上进行的，边界节点查询DS标记字段并将其归入某一特定的流聚集中。DS模型中边界调节分类的部分主要包括：1、接纳控制(Admission Control)，判断是否有足够的资源来支持相应类型的控制。2、包分类器(Packet Classifier)，确定源地址、目的地址、端口字段，判断包的类型。3、包调度器(packet Scheduler)，用来调度包的发送。在调度器中，负责主要的包流量的整形与调度，提供标记器(Marker)、计量器(Meter)、丢包器(Dropper)三部分。由标记器对IP包头进行标记，计量器和丢包器主要进行排队发送等工作PHB是一个DS节点调度转发处理包头标有DS标记的IP包流的外部行为描述。在DS字段内，转发节点是按照PHB来进行的，在每一传输段逐段保证PHB行为是区分服务的最大特点，也是区分服务分段保证端到端QoS的基础。PHB可以用一系列流的参数特性包括延迟、抖动、优先级等来描述。由于不同的PHB流同时传输，因而就存在流的竞争问题。当前边界节点与内部节点中流聚集的竞争与公平性问题一直是研究的热点问题。与多媒体传输中自适应思想相结合的调节方法将是发展的趋势。IETF已经标准化了一部分PHB，包括BE（Best Effort）、加速型转发（EF，Expedited Forwarding）、确保型转发（AF，Assured Forward）及兼容IP优先级的类型选择型（CS，Class Selecter）四种，缺省PHB为BE。RFC文档中关于网络系统中PHB定义为：每跳转发行为。PHB指对于某种dscp，实际上是DiffServ网络节点给不同dscp分配资源的方法，不同的PHB对应不同的缓冲区管理和分组调度机制。Internet中能实现区分服务的连续区域被称为DS域（DS Domain），在一个DS域中，服务提供策略（Service Provisioning Policies）和逐跳行为（Per-Hop Behavior，PHB）都是一致的。PHB是DS节点对一个分组的转发行为。IETF定义了4种PHB:(1)默认转发(Default Forwarding，简称DF)(2)确保转发AF(Assured Forwarding)：该区分服务中，定义了4级AF(AFl～AF4)，每级AFx定义了3个等级，即包含了12个PHB，在DS节点中为每一级AF都分配一定数量的转发资源(如带宽、缓冲区)。对于属于同一种AF的数据包，每个DS节点对它们都采用FIFO策略进行调度，同时对于同一类AF的数据包，又可以有3种不同的拥塞丢弃优先级，级别越高的AF越早被节点处理，当发生拥塞时，其转发成功率越高。值得注意的是，确保转发能确保IP分组能转发出去而不丢失，即当IP分组数据流超过本地策略规划的流量时，IP分组数据流将被降级，转发时延会增加，但不会丢弃。(3)迅速转发模式(Expedited Forwarding，简称EF)：该模式中包含1个PHB，利用EF PHB可以在Ds域中实现低时延，低时延抖动和低丢弃率，并具有一定带保证的端到端业务，这种业务也称之为优质业务(Premium Services)。(4)Class Selector(CSx，x=0，1，…，7)，包含了8个PHB。新手上路成长任务编辑入门编辑规则本人编辑我有疑问内容质疑在线客服官方贴吧意见反馈投诉建议举报不良信息未通过词条申诉投诉侵权信息封禁查询与解封©2024 Baidu 使用百度前必读 | 百科协议 | 隐私政策 | 百度百科合作平台 | 京ICP证030173号京公网安备110000020000

聚β-羟丁酸

经法医检验，β-羟丁酸是该塑料袋体内的高分子化合物聚β-羟丁酸的分解产物······

聚β-羟丁酸（简称PHB）

PHB是一种存在于许多细菌细胞质内属于脂质的碳源类贮藏物，不溶于水，而溶于氯仿，可用尼罗蓝或苏丹黑染色，具有贮藏能量、碳源和降低细胞内渗透压等作用。由于PHB是由生物合成的高聚物，具有无毒、可塑和易降解等特点。其在活性污泥中降解需要几个月，海水中需要几年；在生物体内可参与细胞的能量和物质代谢，最终转化为二氧化碳和水。

PHB自1925年在B.megaterium中被发现以来，至今已在60属以上的细菌中确定其存在，在很多类细菌中都有较高产量，属于微生物合成类高分子。

性质

PHB为热塑性聚酯，物理性质与结构与聚丙烯相似（熔点、玻璃态温度、结晶度、抗张强度等）化学结构规整。结晶度高达60~80%，相对密度大、透氧率低、抗紫外线照射、具光学活性，但易脆、易断裂。可通过生物、化学、物理方法对之进行改性。

应用

可用于制作不污染环境的生物可降解塑料，合成光学材料和磁粉，制造生物纳米材料，也有用于材料的改性加工等很多方面。

微生物合成类高分子

微生物合成高分子是由微生物发酵法制成的一类材料,主要包括聚酯和多糖,如:真氧产碱杆菌可以利用果糖、木糖、延胡索酸、衣糠酸、丙酸、乳酸作为碳源生产PHB(聚一3一羧基丁酸酯)。具有代表性的是聚B一羟基烷酸(PHAs)系列聚酯。

微生物的合成机理是通过用葡萄糖或淀粉类对微生物进行喂养,使它在体内吸收并发酵合成出两类高分子,一类是微生物多糖,一类是微生物聚酯,它们都具有生物降解性。微生物聚酯具有良好的物理性能、成型性能、热稳定性能等,可以制成薄膜,容器等。

Enhanced polyhydroxybutyrate (PHB) production by newly isolated rare actinomycetes Rhodococcus sp. strain BSRT1-1 using response surface methodology | Scientific Reports

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Enhanced polyhydroxybutyrate (PHB) production by newly isolated rare actinomycetes Rhodococcus sp. strain BSRT1-1 using response surface methodology

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Published: 21 January 2021

Enhanced polyhydroxybutyrate (PHB) production by newly isolated rare actinomycetes Rhodococcus sp. strain BSRT1-1 using response surface methodology

Chanaporn Trakunjae1,3, Antika Boondaeng1, Waraporn Apiwatanapiwat1, Akihiko Kosugi2, Takamitsu Arai2, Kumar Sudesh3 & …Pilanee Vaithanomsat1 Show authors

Scientific Reports

volume 11, Article number: 1896 (2021)

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AbstractPoly-β-hydroxybutyrate (PHB) is a biodegradable polymer, synthesized as carbon and energy reserve by bacteria and archaea. To the best of our knowledge, this is the first report on PHB production by a rare actinomycete species, Rhodococcus pyridinivorans BSRT1-1. Response surface methodology (RSM) employing central composite design, was applied to enhance PHB production in a flask scale. A maximum yield of 3.6 ± 0.5 g/L in biomass and 43.1 ± 0.5 wt% of dry cell weight (DCW) of PHB were obtained when using RSM optimized medium, which was improved the production of biomass and PHB content by 2.5 and 2.3-fold, respectively. The optimized medium was applied to upscale PHB production in a 10 L stirred-tank bioreactor, maximum biomass of 5.2 ± 0.5 g/L, and PHB content of 46.8 ± 2 wt% DCW were achieved. Furthermore, the FTIR and 1H NMR results confirmed the polymer as PHB. DSC and TGA analysis results revealed the melting, glass transition, and thermal decomposition temperature of 171.8, 4.03, and 288 °C, respectively. In conclusion, RSM can be a promising technique to improve PHB production by a newly isolated strain of R. pyridinivorans BSRT1-1 and the properties of produced PHB possessed similar properties compared to commercial PHB.

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IntroductionPetrochemical-derived plastics have many applications. Global economic growth and improvement in living standards has led to an increase in purchasing power, which has contributed to an increase in plastic production1. Although traditional petrochemical-derived plastic products have increased the quality of everyday life, they account for the accumulation of municipal waste, which persists undegraded for decades in the ecosystem2. Because of these challenges biodegradable plastics with lower or no negative impact on the environment have gained attention as replacements for petrochemical-derived plastics.

Polyhydroxyalkanoates (PHAs) is an intracellular storage compound accumulated as energy reserve by some microorganisms under stress3,4. PHA has thermo-mechanical properties similar to petrochemical polymers, such as polypropylene (PP) and polyethylene (PE)5,6. Based on their biodegradable, thermoplastic, and mechanical properties, PHAs are expected to replace petrochemical-derived plastics7,8,9. Among 150 PHA monomers10, poly-β-hydroxybutyrate (PHB), the most commonly synthesized form of PHA, has attracted more attention than others due to its physical, mechanical, and immunological properties, which make it an ideal candidate for applications in agriculture, food, and medicine11,12.In addition to PHB producers, such as Cupriavidus necator, Bacillus sp., Pseudomonas sp., and Escherichia coli transformants13,14,15,16, certain actinomycetes also accumulate PHB granules. Studies on PHB production and degradation by Streptomyces, which is the dominant genus of actinomycete, have been reported17,18. However, only a few studies on PHB production by the rare actinomycete genus Rhodococcus have been conducted. Members of the Rhodococcus are widely distributed in nature; they have been isolated from soil, water, marine sediments, and other sources19. They belong to the non-sporulating and mycolic acid-rich group within actinomycetes, together with other related genera, including Mycobacterium, Nocardia, Corynebacterium, and Gordonia20. Rhodococcus is an excellent candidate for bioremediation and bioconversion because it can significantly degrade and transform a wide variety of natural organic and xenobiotic compounds via diverse catabolic pathways21. Additionally, Members of Rhodococcus, such as R. aetherivorans21, R. ruber22, R. equi23, and R. jostii24, produce PHAs using various carbon sources, including sugars, oils, hydrocarbons, and agricultural waste. However, R. pyridinivorans, which was isolated in this study, has not been reported to be a PHA producer.Optimization of fermentation medium is critically investigated because it plays a critical role in cell growth and expression of preferred metabolite affecting overall productivity25. It should be carried out before large-scale metabolite production. Various non-statistical and statistical techniques for medium optimization have been studied extensively. The non-statistical, one-factor-at-a-time (OFAT) approach is identifies significant parameters and their effective ranges. However, OFAT requires numerous experiments to explain the effect of individual parameters and is time consuming. Moreover, it rarely evaluates the effect of more than one factor and its interactions at a time, which is a disadvantage once the interactions of parameters are significant26. Thus, statistical experimental design methods are required to provide statistical models, which investigate several independent variables simultaneously and characterize the relationship between the variables27. Response surface methodology (RSM) is a statistical optimization method, which employs experimental factorial designs, such as central composite design (CCD), for optimizing process yield and defines the behavior of the response in the selected design space28,29. CCD is used to study the interaction effect of the factors that significantly affect product formation. The experimental runs of CCD work as inputs for RSM in finding the mathematical model that links process parameters and outcome30.The aim of this study was to isolate and identify PHB-producing bacteria from the soil, optimize the fermentation medium components by using RSM to enhance PHB production as well as PHB characterization, and to improve the cellular biomass of PHB-producing bacteria in a 10 L stirred-tank bioreactor.ResultsIsolation and screening of PHB-producing bacteriaA total of 79 bacterial strains were successfully isolated from the wastewater treatment area of Kasetsart University, Bangkok, Thailand. Nile red agar plates were used for preliminary screening to select PHB-producing strains. Ten strains exhibited bright orange fluorescence under UV light after being incubated on MM agar containing 1% (w/v) glucose supplemented with Nile red for 3 days (data not shown). However, BSRT1-1 accumulated the highest amount of PHB, at 18 wt% DCW, when cultured in PHB production medium. BSRT1-1 colonies were opaque and raised, with regular configuration. BSRT1-1 produced orange colonies when grown on NA and TSA agar plates at room temperature (35 °C). Microscopic examination revealed that BSRT1-1 cells were Gram-positive, non-spore-forming, and non-motile with a rod–coccus morphology. Cells were short rods during the exponential growth phase and converted to cocci during the stationary growth phase.Identification of PHB-producing bacteria by 16S rRNA geneTo identify BSRT1-1, the 16S rRNA gene of strain BSRT1-1 was extracted and sequenced. The sequence of the 16S rRNA gene (1,483 bp) was obtained and used for the initial BLAST search. Blast analysis of 16S rRNA gene sequence of BSRT1-1 revealed significant similarity with that of R. pyridinivorans DSM44555T (99.86%), R. biphenylivorans TG9T (98.45%), R. gordoniae DSM 44689T (99.17%), and R. lactis DW151BT (98.81%). To determine the taxonomic position of BSRT1-1, a phylogenetic analysis was performed to compare its 16S rRNA gene sequence with that of other species of Rhodococcus. The strain BSRT1-1 formed a coherent clade with R. pyridinivorans DSM44555T in the NJ phylogenetic tree reconstructed using 16S rRNA gene sequences from various strains of Rhodococcus. BSRT1-1 also formed a cluster with the type strains of R. pyridinivorans (Fig. 1). Rhodococcus species, such as R. aetherivorans20 and R. equi23, produce PHB.Figure 1Neighbor-joining tree, based on 16S rRNA gene sequences, showing the position of BSRT1-1 and closely related species of Rhodococcus. Numbers at nodes indicate levels of bootstrap support (%) based on neighbor-joining analysis of 1000 resampled datasets; only values ≥ 50% are given. Filled circles indicate branches of the tree that were also recovered using the maximum-parsimony and maximum-likelihood tree-making algorithms. Corynebacterium diphtheriae NCTC 11397 T (GenBank Accession No. X84248) was used as an outgroup. Bar, 0.01 substitutions per site.Full size imageSelection of carbon and nitrogen sourcePHA biosynthesis was performed in a 250-mL flask to evaluate PHB production in R. pyridinivorans BSRT1-1 and to select the best carbon and nitrogen source for further optimization studies. BSRT1-1 was cultured under nitrogen-limiting conditions using various carbon and nitrogen sources. Of six carbon sources, i.e., glucose, fructose, sucrose, glycerol, molasses, and oil palm, fructose was found to be the best carbon source for PHB production. Therefore, fructose was selected as the carbon source for optimization experiments. BSRT1-1 could grow and accumulate up to 22 wt% DCW PHB when using 30 and 0.5 g/L of fructose and NH4Cl as carbon and nitrogen source, respectively (Fig. 2A). Approximately 1–2.5 g/L of DCW and 6–22 wt% DCW of PHB content were achieved using glucose, fructose, sucrose, molasses, and oil palm as a carbon source, whereas only 0.4 g/L of DCW was obtained when using glycerol as a carbon source. Thus, in addition to simple sugars (monosaccharides), BSRT1-1 could use other carbon sources, such as molasses and oil palm, for cell growth and PHB production (Fig. 2A).Figure 2Poly-β-hydroxybutyrate (PHB) production by Rhodococcus pyridinivorans BRST1-1 using different carbon and nitrogen sources in shake flask experiments.Full size imageNitrogen source is also an important parameter for PHB accumulation. The effects of various nitrogen sources, such as yeast extract, malt extract, peptone, urea, (NH4)2SO4, NH4Cl, NH4NO3, and KNO3, on cell growth and PHB production by BSRT1-1 were tested (Fig. 2B). A maximum biomass and PHB content of 1.47 g/L and 32.2 ± 4 wt% DCW were obtained when 0.5 g/L of potassium nitrate (KNO3) and 30 g/L of fructose were used as a nitrogen source and carbon source, respectively. Therefore, KNO3 was used as a nitrogen source for optimization experiments.Optimization of PHB accumulation by RSMA three-variable-five-level design of CCD was used to determine the optimized medium composition for PHB accumulation and the interactive effects of each parameter. Fructose, KNO3, and TE solution were selected as the parameters for CCD. The response data were analyzed by the Design-Expert v7.0.0 software (Stat-Ease, Inc. MN, USA). The experimental results of PHB content and predicted responses are shown in Table 1. The results indicated that the highest PHB content, 42.9 wt% DCW, was obtained when the concentrations of fructose, KNO3, and TE solution were 20, 1.0, g/L, and 1.0 mL/L, respectively. The lowest PHB content was 17.4 wt% DCW, when the concentrations of fructose, KNO3, and TE solution were 3.20, 1.0, g/L, and 1.0 mL/L, respectively. The results obtained from multiple regression analyses of CCD experiments were fitted to a second-order polynomial model. PHB content fitted in terms of coded variables was obtained as the following model:$$ \begin{aligned} {\mathrm{Y}} & = 42.67 - 0.36{\mathrm{X}}1 - 2.55{\mathrm{X}}2 - 3.28{\mathrm{X}}3 - 8.42{\mathrm{X}}1{\mathrm{X}}2 + 0.95{\mathrm{X}}1{\mathrm{X}}3 - 2.21{\mathrm{X}}2{\mathrm{X}}3 \\ & \quad - 6.65{\mathrm{X}}1^{2} - 4.02{\mathrm{X}}2^{2} - 2.91{\mathrm{X}}3^{2} \\ \end{aligned} $$

where Y is the PHB content and X1, X2, and X3 are coded values of fructose, KNO3, and TE solution, respectively. The statistical significance of the equation was verified by the F test and the ANOVA for the response surface quadratic model is shown in Table S1. The regression equation presented a determination coefficient, R2 = 0.9011 (Table S1). Thus, this model can explain approximately 90.11% of the variability in the dependent variable; 9.89% was affected by other variables. The R2 value is always between 0 and 1. The closer the R2 to 1.0, the stronger the model and the better it predicts the response31. The adjusted R2, which corrects the R2 value for the sample size and the number of terms, was 0.773932.Table 1 Experimental design and result of central composite design (CCD) of response surface methodology.Full size tableThe P-values are used to check the significance of each coefficient, which help to understand the pattern of mutual interactions between the best variables33. The smaller the P-value, the larger the significance of the corresponding coefficient34. The F test and the corresponding P-values were estimated, as shown in Table 2. The model indicates that the constant linear (X3), quadratic (X12, X22), and interaction terms (X1X2 and X2X3) are significant (p < 0.05) (Table 2). In this model, the negative polynomial coefficient in interaction terms implies that the interaction is antagonistic. Quadratic model analysis shows that the input independent variable of TE solution (X3) was important for PHB accumulation. However, the quadratic terms coded as X12, X22 and their interaction (X1X2) are also significant, with the probability value of p < 0.05, which indicates that the effect of coded variable X1, X2 and their interactions are considerable for PHB accumulation.Table 2 Analysis of variance table.Full size tableTo evaluate the interaction between different parameters and to determine the optimal concentration of each parameter for maximum PHB content, the response between fructose (X1), KNO3 (X2), and TE solution (X3) was plotted, as shown in the Fig. 3. Figure 3A shows the effect of fructose and KNO3 on PHB content. PHB content increased when fructose concentration increased from 30.0 to 35.0 g/L. At a higher fructose concentration (> 35.0 g/L), PHB content declined. PHB content increased with decreasing KNO3 concentration, from 0.5 to 0.3 g/L. At a high KNO3 concentration (> 0.3 g/L) PHB content declined. The effect of fructose and TE solution on PHB content is shown in Fig. 3B. PHB content increased with decreasing fructose, from 30.0 to 29.0 g/L. PHB content declined at a higher concentration of fructose (> 29.0 g/L), whereas PHB content increased with an increase in TE concentration, from 0.5 to 0.6 mL/L. PHB content declined at a higher concentration of TE solution (> 0.6 mL/L). The effect of KNO3 and TE solution are shown in Fig. 3C. PHB content increased with decreased KNO3, from 0.50 to 0.45 g/L. PHB content decreased at a higher concentration of KNO3 (> 0.45 g/L) and increased with increased concentration of TE solution, from 0.5 to 0.75 mL/L. PHB content declined when TE solution was at > 1.0 mL/L.Figure 3Response surface and contour plots described by the model, representing poly-β-hydroxybutyrate (PHB) accumulation (wt% DCW) as a value of fructose, KNO3, and TE solution by Rhodococcus pyridinivorans BRST1-1. Combined effect of fructose and KNO3 (A); fructose and TE solution (B); KNO3 and, TE solution (C).Full size imageThe model was validated for the three variables within the design space to confirm the optimization results. Optimized medium composition from RSM was carried out in a 250-flask scale in triplicate. The result shows that under the following conditions: fructose, 33.6 g/L, KNO3, 0.3 g/L, and 1.0 mL/L of TE solution, the maximum PHB content of 43.1 wt% DCW, with 3.2 g/L of DCW, nearing the predicted PHB content of 43.36 wt% DCW. The predicted values and actual experimental values were compared and the residual was calculated. The percentage error between the actual and predicted values for PHB content was 0.31%. Hence, the observed models were reasonably accurate and RSM analysis is a suitable technique for predicting and optimizing the fermentation media.Scaling up PHB production in a 10 L bioreactorTo enhance the biomass and PHB accumulation of R. pyridinivorans BRST1-1, batch cultivation was carried out in a 10 L stirred-tank bioreactor containing 6 L of optimized media (fructose, 33.6 g/L, KNO3, 0.3 g/L, and 1.0 mL/L of TE solution). The temperature, pH, aeration rate, and agitation speed were fixed at 35 °C, 7.0, 0.75 vvm, and 180 rpm, respectively. During 72 h of fermentation, growth of BSRT1-1 showed a predictable exponential phase, followed by PHB accumulation. The quantity of PHB accumulated increased in the fermenter as the fructose levels decreased (Fig. S1). As seen in Fig. S1, the biomass increased gradually over the fermentation period. However, when the fermentation period was extended above the optimum (54 h), with no remaining fructose, PHB accumulation and cell growth were interrupted and the degradation of PHB began35. The highest production of PHB was at 48 h when the DCW was 5.2 ± 0.5 g/L; PHB content was 46.8 ± 2 wt% DCW (Fig. S1).Characterization of PHBFourier Transform IR spectroscopy (FTIR) was performed to investigate the different functional groups of PHB produced by R. pyridinivorans BSRT1-1. The FTIR spectrum of PHB, which was recorded between 4000 and 600 cm−1 (Fig. 4), shows a sharp absorption band at 1721 cm−1 which corresponds to carbonyl (C=O) stretching of the ester and another band at 1277 cm−1, corresponding to the -CH group. The presence of these bands has been reported and labeled as a PHB marker36. While a series of bands between 1,000 and 1,300 cm−1 show stretching of the C–O bond of the ester group37. The bands at 2975 and 2933 cm−1 indicate the presence of methyl (CH3) and methylene (CH2) asymmetric and symmetric stretching modes, respectively. Additionally, bands of minor relevance at 3443.7 cm−1 are related to a terminal OH group38. The 1H NMR was performed to observe the chemical structure of PHB synthesized by the strain BSRT1-1. Figure 5 shows the 1H NMR spectrum of three different signals at 1.29, 2.5, and 5.27 ppm, which were represented methyl, methylene, and methane group, respectively, confirming its structure as a PHB39,40. Thermal properties of PHB synthesized by strain BSRT1-1 was performed by using DSC and TGA analysis (Fig. 6). DSC was conducted to investigate the melting temperature (Tm) and glass transition (Tg) of PHB. The Tm and Tg of PHB were found to be 171.8 and 4.03 °C, respectively (Fig. 6A). TGA was performed to observe the thermal stability of PHB synthesized by strain BSRT1-1. Figure 6B shows the PHB degradation pattern, which was exhibited a single degradation step under a nitrogen atmosphere, between 240 °C and 400 °C. The result indicates that PHB degradation appears rapidly, marked by a sharp decrease in the curve. The onset temperature of the PHB was at 288 °C. The PHB was completely degraded at 320 °C.Figure 4Fourier transform infrared spectroscopy (FTIR) spectrum of PHB produced by Rhodococcus pyridinivorans BRST1-1.Full size imageFigure 5Proton Nuclear Magnetic Resonance Spectroscopy (1H NMR) spectrum of PHB produced by Rhodococcus pyridinivorans BRST1-1.Full size imageFigure 6Differential Scanning Calorimetry (DSC) and Thermogravimetric analysis (TGA) of PHB produced by Rhodococcus pyridinivorans BRST1-1.Full size imageDiscussionPHB is a currently well-studied type of PHAs, which is an intracellular storage compound accumulated as energy reserve material by bacteria and archaea under different stress conditions3,4. In the present study, potential PHB accumulating bacteria were successfully isolated from the wastewater treatment area of Kasetsart University, Bangkok, Thailand. Preliminary screening of PHB-producing strains was further identified by a Nile red agar plates method41. This method has been used commonly for the rapid identification of PHA-producing bacteria, but not yet with archaea42. Among all PHB-producing isolated strain, the strain BSRT1-1 was found to be the best PHB producer, which was accumulated the highest amount of PHB, at 18 wt% DCW, when cultured in PHB production medium using glucose and NH4Cl as a carbon and nitrogen source, respectively. The present study shows that the habitats of the wastewater treatment area were a potential source for bacterial isolates producing PHB. Many studies have been reported on the isolation of PHA-producing bacteria from wastewater treatment sources. Yan et al.43 have been isolated PHA-accumulating bacteria from activated sludge samples collected from municipal wastewater treatment plants in Quebec by using acetate as sole carbon source. Besides, Bhuwal et al.44 reported the use of pulp, paper, cardboard industry sludge, and wastewater for the isolation and screening of PHA accumulating bacteria. Additionally, Jinda and Paniticharoenwong45 have been successfully isolated PHA-producing bacteria, Ralstonia sp. NBKT10 frm the soil of palm oil manufacturing plants.Comparison of the bacterial 16S rRNA gene sequence has emerged as a preferred molecular technique to the identification of bacteria that has replaced the conventional techniques that rely on phenotypic identification46. In this study, the most excellent PHB producer strain, BSRT1-1, was identified based on the 16S rRNA gene as Rhodococcus pyridinivorans. The R. pyridinivorans was first isolated as a pyridine-degrading coryneform bacterium from industrial wastewater in Korea47. This species has been reported the ability to degrades various type of aromatic compounds, for example, pyridine47, styrene48, as well as BTX (benzene, toluene, and xylene)49. However, interestingly, this is the first report on PHB production by R. pyridinivorans strain BSRT1-1.The effect of various carbon and nitrogen sources on PHB production was investigated by using OFAT method. R. pyridinivorans BSRT1-1 could grow and accumulate the maximum PHB of 32.19 ± 3.86 wt% DCW when using 30 and 0.5 g/L of fructose and potassium nitrate as carbon and nitrogen source, respectively. Therefore, fructose and potassium nitrate were used for optimization experiments. This finding is supported by the previous report, where fructose has been reported as a suitable substrate for PHB production in Alcaligenes eutrophus50. Similarly, Aquitalea sp. USM4 can accumulate up to 27 wt% of PHA when 10 g/L of sugars such as glucose, fructose, and sucrose are used as a carbon source51. In comparison, toluene and crude palm kernel oil are used as a carbon source for PHA production by R. aetherivorans20 and R. equi22, respectively. Both organic and inorganic nitrogen sources were attempted to enhance the nitrogen source for PHB production. In this study, potassium nitrate, an inorganic nitrogen source, supported to produce the highest amount of PHB. Contrary to this, urea has been reported as a suitable nitrogen source for PHB production by Aquitalea sp. USM451 and Pseudomonas aeruginosa52. While the highest level of PHB accumulation by Bacillus subtilis 25 and Bacillus megaterium 12 was observed in a medium using an organic nitrogen source, protease peptone53.RSM employing CCD was applied to improve the production of PHB in a flask scale. The highest yield of 3.60 ± 0.5 g/L in biomass and 43.1 ± 0.5 wt% of dry cell weight (DCW) of PHB were achieved when using RSM optimized medium, which was increased the production of biomass and PHB content by 2.5 and 2.3-fold, respectively. Previously, RSM has been reported as a powerful tool to improve the production of PHB by various microorganisms. Higher concentrations of PHB can be produced from glucose by a newly engineered strain of C. necator NSDG-GG using RSM26. PHB production by Methylobacterium sp has been successfully enhanced by RSM using methanol as a sole carbon source54. RSM is useful in improving PHB production by the B. drentensis strain BP17 using pineapple peel as a sole carbon source55. Hassan et al.56 have been reported the efficient optimization of PHB production by novel Bacillus subtilis from rice bran using RSM employing Box–Behnken design. Moreover, RSM enhances the production of PHA copolymers, such as poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV). The development of PHBV production using sugarcane molasses supplemented with the co-substrates palm oil and corn steep liquor as a carbon source is reported for the yeast strain, Wickerhamomyces anomalus VIT-NN0157. Besides, RSM has been used to evaluate the optimum operating condition for PHBV-tapioca starch composites58. However, when comparing PHB production by R. piridinivorans BSRT1-1 with C. necator, which is industrially important strain for PHB production, under nutrient limitation with an excess of carbon, C. necator accumulated PHA (mainly PHB) up to 90% of its DCW59, whereas R. piridinivorans BSRT1-1 can accumulate 43% PHB of its DCW when using RSM optimized medium. Nevertheless, the enhancement of biomass to improve PHB production by R. piridinivorans BSRT1-1 can be achieved by scaling up PHB production in a 10 L bioreactor.The PHB production in a 10 L stirred-tank bioreactor can improve the production of biomass by 1.4. Thus, significantly higher biomass could be obtained in a larger scale bioreactor. The improvement of PHB production using batch fermentation by various types of bacteria has been reported60,61,62. However, in this present study PHB accumulation cannot be increased by this approach due to the disadvantages of single batch fermentation35. Batch fermentations are the most popular and straightforward method for PHB production, however inherently low yield. The maximum permitted concentration of nutrients is limited by the physiological requirements of the processing strain at the beginning of the fermentation batch2.The extracted PHB was characterized by FTIR, NMR, DSC and TGA techniques. The observed band in the FTIR spectrum at 1721 cm−1, 1277, 1000–1300, 2975, 2933, and 3443.7 cm-1 represented C=O ester, -CH, C–O, CH3, CH2, and OH groups of the polymer, respectively. The obtained FTIR analysis is similar to the previous reports36,37,38,39. Additionally, three different signals of 1H NMR spectrum at 1.21, 2.56, and 5.22 ppm represented methyl, methylene, and methane groups, respectively, which were confirmed the chemical structure of the PHB40. Thermal analyses showed that the extracted PHB existed as a thermally stable semi-crystalline polymer55, the Tm and Tg of extracted PHB were 171.8 and 4.03 °C, respectively. Similar Tm and Tg have been previously reported in PHB63,64,65. The maximum thermal decomposition observed was at 288 °C by FIIR and is related with the ester cleavage of PHB by b-elimination reaction67. Many researchers have been reported similar TGA results of PHB55,63,64,65,66. All these results confirmed that the polymer produced by R. pyridinivorans BSRT1-1 is PHB homopolymer, and the properties of extracted PHB were similar to the commercial PHB68.ConclusionsThe strain R. pyridinivorans BSRT1-1 was isolated from soil and identified as the first PHB producer in R. pyridinivorans. Fructose and KNO3 were found to be the best carbon and nitrogen sources for PHB production by this strain, respectively. Under optimum conditions, obtained from RSM, this strain can accumulate 43.1 wt% DCW of PHB and produce 3.60 ± 0.5 g/L of biomass. The optimized medium can improve the production of biomass and PHB content by 2.5 and 2.3-fold when compared to un-optimized medium. Therefore, RSM is a powerful tool for optimizing PHB production. Furthermore, higher biomass of 5.2 ± 0.5 g/L and PHB content of 46.8 ± 2 wt% DCW were achieved from the 10 L stirred-tank bioreactor. Finally, the functional group and chemical structure results verified the polymer as PHB and the thermal properties of produced PHB possessed similar properties compared to commercial PHB.Materials and methodsSample collectionA total of 12 soil samples were randomly collected from the wastewater treatment area of Kasetsart University, Bangkok, Thailand (latitude: 13.854529N, longitude: 100.570012 E). All soil samples were kept in sterilized envelopes and brought to the laboratory. Each sample was air-dried at room temperature (35 °C) for 1–2 days, crushed, and mixed.Medium and inoculum preparationThe minimal medium (MM) for PHB production consisted of NH4Cl, 0.5 g/L; KH2PO4, 2.8 g/L; Na2HPO4, 3.32 g/L; MgSO4·7H2O, 0.25 g/L, and 1 mL/L of trace element (TE) solution. The TE solution comprised: ZnSO4·7H2O, 1.3 g/L; FeSO4·7H2O, 0.2 g/L; (NH4)6Mo7O24·4H2O, 0.6 g/L; H3BO3, 0.6 g/L, and CaCl2, 0.2 g/L. The sugars were sterilized at 110 °C for 20 min and then aseptically added into the flask containing other components. The pH of the final culture medium was adjusted to 7.0 before bacterial inoculation. The inoculum of the selected strain was prepared by inoculating a full loop of a single colony in a 250 mL Erlenmeyer flask containing 50 mL of Tryptic Soy Broth (TSB) (BD, Franklin Lakes, NJ, USA). The culture incubated at 35 °C with shaking at 180 rpm for 24 h. The cells were harvested by centrifugation at 8,000 g at 4 °C for 10 min. The cell pellet was washed with sterile 0.85% (w/v) NaCl. The optical density of cell suspension was adjusted using 0.85% (w/v) NaCl to 0.5–07 at 600 nm. A 10% (v/v) of cell suspension was used as the inoculum.Isolation and screening of PHB-producing bacteriaOne gram of each soil sample was serially diluted in sterile distilled water and plated onto nutrient agar (NA) and TSA plates. All plates were incubated at 37 °C for 3 days. Several individual colonies of different morphologies were picked and the purified isolates were maintained on agar slants of the same medium. All the isolated strains were streaked onto mineral medium (MM) agar plates containing glucose, 30 g/L; Nile red, 0.005% (w/v) (Sigma-Aldrich, St. Louis, MO, USA), and 15 g/L of agar powder to screen for PHB production. The plates were incubated at 37 °C for 1–3 days. Thereafter, colonies with bright orange fluorescence under UV were selected. The isolates were stored at -80 °C in 20% (v/v) glycerol until further use.Identification of PHB-producing bacteria by 16S rRNA geneThe selected PHB-producing isolate was identified based on 16S rRNA sequence. The DNA was extracted using the standard protocol of Sambrook and Russell (2001)69. 16S rRNA gene amplification was carried out using Ex Taq polymerase (TakaRa Bio Inc., Tokyo, Japan). A forward primer (27F): 5′AGA GTTTGATCCTGGCTAG 3′ and reverse primer (1492R): 5′GGCTA CCTTGTTACG ACTT 3′ were used to amplify the gene. The PCR temperature cycling conditions were as follows: initial denaturation at 94 °C for 5 min; 30 cycles of denaturation at 94 °C for 1 min, annealing at 55 °C for 1 min, and elongation at 72 °C for 2 min. The final cycle was followed by extension at 72 °C for 10 min70. The amplification products were purified using the Qiagen PCR purification kit (Qiagen) and subcloned to pTAC-1, followed by transformation into E. coli JM109. Plasmids were extracted with the QIAprep Spin Miniprep kit (Qiagen) and sequenced by MACROGEN (Korea). The GeneBank database in the BLAST program of the National Center for Biotechnology Information was used to compare the sequence of 16S rRNA gene, which was deposited in GenBank. The phylogenetic tree was constructed using the MEGA software version 7.0.Selection of carbon and nitrogen sourceOFAT method was used to investigate the effect of carbon and nitrogen source on PHB production by the selected strain. Briefly, MM medium supplemented with 30 g/L of six carbon sources, i.e., glucose, fructose, sucrose, glycerol, molasses, and oil palm, was inoculated with 10% (v/v) of inoculum and the cultures were grown at 35 °C with shaking at 180 rpm for 72 h. Thereafter, the samples were analyzed and the best carbon source for PHB production was selected and used for nitrogen source studies. To evaluate the effect of the nitrogen source on PHB production, eight nitrogen sources, i.e., yeast extract, malt extract, peptone, urea, (NH4)2SO4, NH4Cl, NH4NO3, and KNO3, were used at a concentration of 0.5 g/L. All experiments were performed in triplicates and average values were determined.Experimental design and statistical modelingIn this experiment, CCD was used to design fermentation experiments. RSM, which is an empirical modeling technique, was applied to evaluate the relationship between a set of controllable experimental factors and observed results. The Design-Expert v7.0.0 software (Stat-Ease, Inc. MN, USA) was used for statistical DOE and the data was analyzed. According to this design, the total number of treatment combinations was 2k + 2k + n0, where k is the number of independent variables and n0 is the number of repetitions of experiments at the center point71. Seventeen fermentation runs were designed based on the CCD of three factors—fructose concentration, X1 (g/L); KNO3 concentration, X2 (g/L); and TE solution volume, X3 (mL/L). Each variable was coded at five levels (− 1.68, − 1, 0, + 1, and + 1.68) to describe the nature of the response surface in the optimum region. The coded and actual levels of the variables are shown in Table 3. The design matrix of the performed fermentation runs is shown in Table 1. The average values were reported from duplicate experimental runs. The coded values were set for three factors, resulting in seven factorial points (including all possible combinations of the maximum and minimum levels), seven axial points (one of the factors set at the midpoint), and three center points (replicated fermentation runs at the factors midpoint). The experimental results of CCD design were fit with a second-order polynomial equation by a multiple regression technique, as shown in Eq. (1).$$ Y = \beta_{0} + \sum\limits_{i = 1}^{k} {\beta_{i} X_{i} } + \sum\limits_{i = 1}^{k} {\beta_{ii} X_{i}^{2} } + \sum\limits_{i < } {\sum\limits_{j = 2}^{k} {\beta_{li} X_{i} X_{j} } } $$

(1)

where Y is the predictive measured response; Xi and Xj are the independent variables; β0 represents the intercept; and βi, βii, and βlj are the regression coefficients of the model72. The generated model for three independent variables is shown in Eq. (2).$$ \begin{aligned} Y & = \beta_{0} + \beta_{1} X_{1} + \beta_{2} X_{2} + \beta_{3} \beta_{3} + \beta_{11} X_{1}^{2} + \beta_{22} X_{2}^{2} + \beta_{33} X_{3}^{2} \\ & \quad + \beta_{12} X_{1} X_{2} + \beta_{13} X_{1} X_{3} + \beta_{23} X_{2} X_{3} \\ \end{aligned} $$

(2)

where Y is the predictive measured response as PHB content (wt% Dry cell weight (DCW)); β1, β2, and β3 are linear coefficients; β11, β22, and β33 denote quadratic coefficients; β12, β13, and β23 are interaction coefficients; X1, X2, and X3 represent coded values of fructose concentration, X1 (g/L); KNO3 concentration, X2 (g/L); and TE solution volume, X3 (mL/L).Table 3 Experimental code and actual levels.Full size tableModel validation and confirmationTo determine the accuracy of the model, the concentrations of three factors (fructose, KNO3, and TE solution), which had a significant influence on PHB production, were randomly selected within the design space to confirm the shake flask model by R. pyridinivorans BRST1-1. The remaining components of the medium in this experiment were at fixed levels.Scale up in the 10 L bioreactorFermentation was evaluated in a 10 L stirred-tank bioreactor (Model MDFT-N-10L, Marubishi, Japan) to enhance the production of biomass and PHB by R. pyridinivorans BRST1-1. The inoculum was prepared in a 500 mL Erlenmeyer flask containing 200 mL of media. Batch cultivation was carried out at 35 °C in a 10 L stirred-tank bioreactor containing 6 L of optimized media. The bioreactor was sterilized in an autoclave at 121 °C for 30 min, cooled, and then inoculated with 10% (v/v) inoculum. The pH of the culture broth was maintained at pH 7.0 by the addition of acid or base by a pH controller. The airflow rate and agitation speed were fixed at 0.75 vvm and 180 rpm, respectively. The cell biomass and PHB content were evaluated every 6 h for 72 h of fermentation. The fermentation experiments were carried out in duplicates and average values were determined.Dry cell weight (DCW) analysisFor the determination of DCW, 1 mL of cell culture suspension was added in triplicate to pre-weighed Eppendorf tubes. The cells were harvested by centrifugation at 8,000 rpm at 4 °C for 10 min. Thereafter, the harvested cells were washed twice by resuspending the cell pellet in distilled water and centrifuged again at 8,000 rpm at 4 °C for 10 min. The washed cell pellet was frozen at − 20 °C overnight. Subsequently, the cell pellet was lyophilized using a freeze-dryer for 2 days. Eppendorf tubes were weighed again to confirm stability and the DCW was calculated in g/L.PHB content analysisThe PHB content was measured as described by Karr et al.73 Briefly, 50 mL of stationary growth phase culture was collected by centrifugation at 8,000 rpm at 4 °C for 10 min. The harvested cells were washed twice with distilled water and frozen overnight at − 20 °C. The dry pellets were boiled in 1 mL concentrated H2SO4 for 60 min, diluted with 4 mL of 0.014 M H2SO4, and filtered through an MCE filter. Samples were analyzed for PHB concentration by high-performance liquid chromatography using an Aminex HPX -87H ion-exclusion column. Crotonic acid (Sigma-Aldrich) was used as a standard. The regression equation obtained from the crotonic acid standard was used to calculate the amount of crotonic acid produced from PHB.PHB extraction and purificationThe PHB accumulated in the cells were extracted using chloroform extraction method which was modified by Hassan et al.74 Briefly, the PHB was extracted by dissolving 1 g of freeze-dried cells in 100 mL chloroform for 3–5 days at room temperature. After that, the solution was filtered using Whatman No. 1 filter paper to remove the cell debris. The filtrate was concentrated to 10 mL using a rotary evaporator followed by drop wise addition into a vigorously stirred 100 mL of chilled methanol. The purified polymer was finally collected, and air dried for 3 days.Fourier transform IR spectroscopy (FTIR)The functional groups of purified PHB were identified by ATR-FTIR spectrophotometer equipped with spectrum (analysis software) for Windows v.10 (PerkinElmer, USA). The following conditions were used: Spectral range, 4000–600 cm−1; window material, CsI; 16 scans; resolution 4 cm−1.Proton nuclear magnetic resonance spectroscopy (1H NMR)The chemical structure of PHB was confirmed by proton nuclear magnetic resonance (1H-NMR) spectroscopy. Around 3 mg of the purified PHB was dissolved in 1 mL of deuterated chloroform (CDCl3) at a concentration of 25 mg/mL using tetramethysilane as an internal chemical shift reference. The 1H-NMR spectra were recorded at 500 MHz on a Bruker AVANCE 500 (NC, USA) spectrometer at 30 °C.Differential scanning calorimetry (DSC) analysisDSC experiments was performed using DSC-60 (Shimadzu, Japan) instrument under a nitrogen flow rate of 30 mL/min. Approximately 5 mg of purified PHB was loaded into an aluminum pan and heated from 25 to 200 °C at a heating rate of 15 °C/min. The melt samples were then maintained at 200 °C for 2 min and followed by rapid quenching to -40 °C. They were heated again from -40 to 200 °C at a heating rate of 15 °C/min. The melting temperature (Tm) and glass transition temperature (Tg) were determined from DSC thermogram.Thermogravimetric analysis (TGA)The thermal degradation temperature of the PHB was analyzed by TGA using instrument STA 6000 (Perkin Elmer, USA). About 5 mg of the purified PHB sample was loaded in aluminum pan and heated from 30 to 920 °C at a heating rate of 20°C/min under nitrogen atmosphere.

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Download referencesAcknowledgementsThis research was financially supported by Kasetsart University Research and Development Institute (KURDI), Japan International Research Center for Agricultural Sciences (JIRCAS), Japan and Kasetsart Agricultural and Agro-Industrial Product Improvement Institute (KAPI).Author informationAuthors and AffiliationsNanotechnology and Biotechnology Research Division, Kasetsart Agricultural and Agro-Industrial Product Improvement Institute (KAPI), Kasetsart University, Bangkok, ThailandChanaporn Trakunjae, Antika Boondaeng, Waraporn Apiwatanapiwat & Pilanee VaithanomsatPost-Harvest Science and Technology Division, Japan International Research Center for Agricultural Sciences (JIRCAS), Tsukuba, Ibaraki, JapanAkihiko Kosugi & Takamitsu AraiSchool of Biological Sciences, Universiti Sains Malaysia, 11800, Gelugor, Penang, MalaysiaChanaporn Trakunjae & Kumar SudeshAuthorsChanaporn TrakunjaeView author publicationsYou can also search for this author in

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PubMed Google ScholarContributionsConception and design of the study by C.T. and P.V.; C.T. conducted the experiment, which was supervised by P.V., A.K., T.A., and K.S.; A.B., and W.A. helped with bacterial identification analysis. Primary draft and revisions by C.T., P.V., and K.S.Corresponding authorCorrespondence to

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