Reconstruction of Acetogenesis Pathway Using Short-Read Sequencing of Clostridium aceticum Genome.
Clostridium aceticum is an anaerobic homoacetogen, able to reduce CO2 to multi-carbon products using the reductive acetyl-CoA pathway. This unique ability to use CO2 or CO makes the microbe a potential platform for the biotech industry. However, the development of genetically engineered homoacetogen for the large-scale production of commodity chemicals is hampered by the limited amount of their genetic and metabolic information. Here we exploited next-generation sequencing to reveal C. aceticum genome. The short-read sequencing produced 44,871,196 high quality reads with an average length of 248 bases. Following sequence trimming step, 30,256,976 reads were assembled into 12,563 contigs with 168-fold coverage and 1,971 bases in length using de Bruijn graph algorithm. Since the k-mer hash length in the algorithm is an important factor for the quality of output contigs, a window of k-mers (k-51 to k-201) was tested to obtain high quality contigs. In addition to the assembly metrics, the functional annotation of the contigs was investigated to select the k-mer optimum. Metabolic pathway mapping using the functional annotation identified the majority of central metabolic pathways, such as the glycolysis and TCA cycle. Further, these analyses elucidated the enzymes consisting of Wood-Ljungdahl pathway, in which CO2 is fixed into acetyl-CoA. Thus, the metabolic reconstruction based on the draft genome assembly provides a foundation for the functional genomics required to engineer C. aceticum.
Sooin
S
Lee
Yoseb
Y
Song
Donghui
D
Choe
Suhyung
S
Cho
Seok Jong
SJ
Yu
Yongseong
Y
Cho
Sun Chang
SC
Kim
Byung-Kwan
BK
Cho
D000595:Amino Acid Sequence; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D003013:Clostridium / Q000235:genetics* / Q000378:metabolism; D004269:DNA, Bacterial / Q000032:analysis / Q000235:genetics; D016680:Genome, Bacterial / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008969:Molecular Sequence Data; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA / Q000379:methods*
D001426:Bacterial Proteins; D004269:DNA, Bacterial