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Auxiliary metabolic genes

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Auxiliary metabolic genes (AMGs) are found in many bacteriophages but originated in bacterial cells. AMGs modulate host cell metabolism during infection so that the phage can replicate more efficiently. For instance, bacteriophages that infect the abundant marine cyanobacteria Synechococcus and Prochlorococcus (cyanophages) carry AMGs that have been acquired from their immediate host as well as more distantly-related bacteria. Cyanophage AMGs support a variety of functions including photosynthesis, carbon metabolism, nucleic acid synthesis and metabolism. AMGs also have broader ecological impacts beyond their host including their influence on biogeochemical cycling.

Classes

AMGs employ diverse functions including pathways not involved in metabolism despite what the name suggests. They are categorized in two classes based on their presence in the Kyoto Encyclopedia of Genes and Genomes (KEGG). AMGs do not encompass metabolic genes involved in typical viral functions, such as nucleotide and protein metabolism since their functions achieve direct viral reproduction, rather than augmenting host function to indirectly enhance it.

Class I

Class I AMGs encode for metabolism pathways in the cell and are found in KEGG. In particular, these genes are found in photosynthesis and carbon metabolism. psbA is almost a ubiquitous photosynthetic AMG for the photosystem Il reaction center D1 found in Synechococcus and Prochlorococcus cyanophages. Photosynthetic machinery for other reaction centers and electron transport are also found in many viruses infecting phototrophs. Phages encode for nearly all genes involved in carbon metabolism. In particular, viruses redirect host metabolism to increase dNTP biosynthesis for viral genome replication. glgA can induce starvation by converting glucose-6-phosphate to glycogen, forcing the host to compensate by deriving ribulose-5-phosphate from glyceraldehyde-3-phosphate and fructose-6-phosphate.

Class II

Class II AMGs encode for peripheral functions absent from the KEGG metabolic pathways. This includes genes typically involved in transport and assembly. Major representatives of this class are involved in balancing TCA cycle intermediates. Additionally, the acquisition of biogenic elements outside of carbon like phosphate, governed by pstS, are prevalent for this class. Confidence of AMG identification for Class II AMGs is reduced without a database for reference.

Abundance

Virus survival through inclusion of AMGs is governed by the laws of natural selection and has been made highly selective through co-evolution with their hosts. As such, the AMGs that confer a fitness advantage to the virus's ability to infect a host and reproduce will be more abundant. AMG abundance is largely dictated by the lifestyle of the virus, environmental conditions surrounding it, and host characteristics.

Lifestyle

Lytic and lysogenic viruses have different lifestyles which impact what AMGs they acquire. Lytic viruses tend to use AMGs to repurpose host cell metabolism and steal nutrients when in high cell density. Therefore, AMGs related to metabolism and transport are found more abundantly in lytic viruses. Lytic viruses also encompass a more diverse set of AMGs than lysogenic viruses, in part due to their larger host range and higher infection frequency. Temperate viruses, on the other hand, may employ AMGs to improve host fitness and virulence due to their often longer lifespan in the cell as a prophage. Gene density in these viruses is higher when compared to their lytic counterparts. Higher rates of HGT in lysogenic viruses allows for more AMG transfer but also lowers overall gene diversity.

Photosynthesis capacity has also been correlated to AMG diversity. Aphotic viral communities possess greater AMG diversity than those in the photic zone.

Environmental conditions

Pathways utilizing nutrients found in low concentrations in the local environment are generally found in higher abundance in the virus. In marine environments, AMGs can confer fitness advantages for both host and viruses under relatively nutrient-limited conditions compared to sediment and strong ultraviolet stress of water. In sunlit versus dark ocean waters, AMGs in distinct pathways are unequally distributed to reprogram host energy production and viral replication based on available nutrients. In sedimentary environments, carbon and sulfur metabolism AMGs are typically more prevalent to outcompete other organisms for the abundant resources.

Host factors

A virus's host range determines which host it can acquire AMGs from. Additionally, the abundance of a host surrounding a virus will affect its likelihood to acquire genes from the host. Virus populations increasingly occupy lytic lifestyles as bacterial production increases. The strong evolutionary connection between viruses and their hosts makes AMG acquisition mirror the host's own adaptation to its environment over time.

Synechococcus and Prochlorococcus are the most abundant picocyanobacteria, accounting for up to 50% of primary production in the marine environment. As such, many AMGs characterized have been discovered in phages of these host systems.

Identification

DRAM-v is the standard for AMG annotation of metagenome assembled genomes (MAGs) identified as viruses. DRAM-v searches the following databases for AMGs that match the input MAGs: Pfam, KEGG, UniProt, CAZy, MEROPS, VOGDB, and NCBI Viral RefSeq. KEGG can then be referenced to classify annotated AMGs through VIBRANT.

Cellular contamination

Since AMGs originate in hosts, distinguishing host and viral genes is critical for their study. This is not easily achieved as cultivation of viral-host systems in a laboratory setting proves challenging if even possible. Additionally, filtering out cellular sequences before entry in bioinformatic pipelines is not possible with cellular gene transfer agents and membrane vesicles are unable to distinguish from viruses due to their many shared properties at this step of analysis. The extent to which they have contaminated existing viral databases is unknown. Some genes have distinctions between host and viral versions such as cyanophage photosynthesis easing the task of computational distinction. The most definitive way developed to determine gene origin has been identification of taxonomically informative genes colocalized on assembled contigs. ViromeQC can display contamination for the dataset overall and DRAM-v assigns a confidence score for the AMG being on a viral MAG. Viral identification is most popularly performed by VIBRANT, VirSorter2, DeepVirFinder, and CheckV.

Genomic context

AMGs are not randomly distributed throughout genomes. Current research is being done to determine the genes that most commonly surround specific AMGs. Hyperplastic regions including the region between genes g15-g18 has been classified as locales where multiple AMGs have been inserted. Possible AMG contexts can be divided into locally collinear blocks (LCBs), or homologous regions shared by multiple viruses without rearrangements. AMGs have been found in just one or up to 14 LCBs. Those found in more diverse contexts have also shown up in variable locales within the LCB.

Acquisition mechanisms

Horizontal gene transfer (HGT) from host to virus allows for AMGs to be acquired. Gene transfer from host eukaryotes to viruses occur about twice as frequently as virus to host gene transfers due to a higher number viral recipients than donors. The vast majority of gene transfer occurs in double-stranded DNA viruses since they have large and flexible genomes, co-evolution with eukaryotes, and wide host breadth. Additionally, unicellular hosts more commonly transfer genes.

Mechanisms of action

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Transcriptional regulation

AMGs may influence gene expression by modulating the activity of transcription factors, which control the rate at which specific genes are transcribed into mRNA, thereby impacting the levels of corresponding proteins involved in metabolic pathways.

Enzyme modulation

Certain AMGs encode proteins that directly interact with enzymes involved in metabolic reactions. This interaction can either enhance or inhibit enzyme activity, leading to changes in the rate of metabolic flux through specific pathways.

Signaling pathways

AMGs may be integrated into cellular signaling pathways, influencing the transmission of signals related to energy status, nutrient availability, or stress. By modulating these signaling pathways, AMGs can indirectly regulate metabolic processes.

Ecological implications

Biogeochemical cycling

AMGs have a large impact on biogeochemical cycles in multiple environments through nutrient degradation, mineralization, transportation, assimilation, and transformation. By enhancing the metabolic capabilities of their hosts, bacteriophages contribute to the recycling of organic matter, influencing the availability of nutrients for other organisms in the ecosystem. Lytic viruses in particular have been shown to increase ammonium oxidation, nitric oxide reduction, nitrification, and denitrification to balance nutrient levels in nitrogen polluted environments. Nutrient-enriched wetlands contain AMGs related to sulfur transport and metabolism. AMG modification of host processes is another means other than the viral shunt by which viruses can directly impact biogeochemical cycles.

Community structure

The ability of AMGs modulating the metabolic capacities of their hosts can influence the abundance and distribution of specific microbial taxa. In turn, this shapes the overall composition of microbial communities, with potential cascading effects on higher trophic levels.

Adaptation to environment

AMGs play a crucial role in microbial adaptation to environmental changes. In extreme environments, AMGs can encode for alternate energy pathways such as subunits of dissimilatory sulfite reductase. The ability of viruses to confer new metabolic traits to their hosts enhances the resilience of microbial communities facing shifts in temperature, nutrient availability, or other environmental stressors. AMGs can also serve as a genetic pool in shaping the evolution of their hosts.

References

  1. Breitbart MY, Thompson LR, Suttle CA, Sullivan MB (2007). "Exploring the Vast Diversity of Marine Viruses" (PDF). Oceanography. 20 (2): 135–139. doi:10.5670/oceanog.2007.58.
  2. Crummett LT, Puxty RJ, Weihe C, Marston MF, Martiny JB (December 2016). "The genomic content and context of auxiliary metabolic genes in marine cyanomyoviruses". Virology. 499: 219–229. doi:10.1016/j.virol.2016.09.016. PMID 27693926.
  3. Mann NH, Cook A, Millard A, Bailey S, Clokie M (August 2003). "Marine ecosystems: bacterial photosynthesis genes in a virus". Nature. 424 (6950): 741. Bibcode:2003Natur.424..741M. doi:10.1038/424741a. PMID 12917674. S2CID 4411495.
  4. Thompson LR, Zeng Q, Kelly L, Huang KH, Singer AU, Stubbe J, Chisholm SW (September 2011). "Phage auxiliary metabolic genes and the redirection of cyanobacterial host carbon metabolism". Proceedings of the National Academy of Sciences of the United States of America. 108 (39): E757–E764. doi:10.1073/pnas.1102164108. PMC 3182688. PMID 21844365.
  5. Enav H, Mandel-Gutfreund Y, Béjà O (March 2014). "Comparative metagenomic analyses reveal viral-induced shifts of host metabolism towards nucleotide biosynthesis". Microbiome. 2 (1): 9. doi:10.1186/2049-2618-2-9. PMC 4022391. PMID 24666644.
  6. ^ Luo XQ, Wang P, Li JL, Ahmad M, Duan L, Yin LZ, et al. (November 2022). "Viral community-wide auxiliary metabolic genes differ by lifestyles, habitats, and hosts". Microbiome. 10 (1): 190. doi:10.1186/s40168-022-01384-y. PMC 9636769. PMID 36333738.
  7. ^ Hurwitz BL, U'Ren JM (June 2016). "Viral metabolic reprogramming in marine ecosystems". Current Opinion in Microbiology. Environmental microbiology * Special Section: Megaviromes. 31: 161–168. doi:10.1016/j.mib.2016.04.002. PMID 27088500.
  8. ^ Brum JR, Sullivan MB (March 2015). "Rising to the challenge: accelerated pace of discovery transforms marine virology". Nature Reviews. Microbiology. 13 (3): 147–159. doi:10.1038/nrmicro3404. PMID 25639680. S2CID 32998525.
  9. Sullivan MB, Lindell D, Lee JA, Thompson LR, Bielawski JP, Chisholm SW (July 2006). "Prevalence and evolution of core photosystem II genes in marine cyanobacterial viruses and their hosts". PLOS Biology. 4 (8): e234. doi:10.1371/journal.pbio.0040234. PMC 1484495. PMID 16802857.
  10. Thompson LR, Zeng Q, Kelly L, Huang KH, Singer AU, Stubbe J, Chisholm SW (September 2011). "Phage auxiliary metabolic genes and the redirection of cyanobacterial host carbon metabolism". Proceedings of the National Academy of Sciences of the United States of America. 108 (39): E757–E764. doi:10.1073/pnas.1102164108. PMC 3182688. PMID 21844365.
  11. Sullivan MB, Coleman ML, Weigele P, Rohwer F, Chisholm SW (May 2005). "Three Prochlorococcus cyanophage genomes: signature features and ecological interpretations". PLOS Biology. 3 (5): e144. doi:10.1371/journal.pbio.0030144. PMC 1079782. PMID 15828858.
  12. Hurwitz BL, Brum JR, Sullivan MB (February 2015). "Depth-stratified functional and taxonomic niche specialization in the 'core' and 'flexible' Pacific Ocean Virome". The ISME Journal. 9 (2): 472–484. Bibcode:2015ISMEJ...9..472H. doi:10.1038/ismej.2014.143. PMC 4303639. PMID 25093636.
  13. ^ Irwin NA, Pittis AA, Richards TA, Keeling PJ (February 2022). "Systematic evaluation of horizontal gene transfer between eukaryotes and viruses". Nature Microbiology. 7 (2): 327–336. doi:10.1038/s41564-021-01026-3. PMID 34972821. S2CID 245616252.
  14. ^ Brum JR, Hurwitz BL, Schofield O, Ducklow HW, Sullivan MB (February 2016). "Seasonal time bombs: dominant temperate viruses affect Southern Ocean microbial dynamics". The ISME Journal. 10 (2): 437–449. Bibcode:2016ISMEJ..10..437B. doi:10.1038/ismej.2015.125. PMC 4737935. PMID 26296067.
  15. Howard-Varona C, Hargreaves KR, Abedon ST, Sullivan MB (July 2017). "Lysogeny in nature: mechanisms, impact and ecology of temperate phages". The ISME Journal. 11 (7): 1511–1520. Bibcode:2017ISMEJ..11.1511H. doi:10.1038/ismej.2017.16. PMC 5520141. PMID 28291233.
  16. Hurwitz BL, Westveld AH, Brum JR, Sullivan MB (July 2014). "Modeling ecological drivers in marine viral communities using comparative metagenomics and network analyses". Proceedings of the National Academy of Sciences of the United States of America. 111 (29): 10714–10719. Bibcode:2014PNAS..11110714H. doi:10.1073/pnas.1319778111. PMC 4115555. PMID 25002514.
  17. Hurwitz BL, Hallam SJ, Sullivan MB (November 2013). "Metabolic reprogramming by viruses in the sunlit and dark ocean". Genome Biology. 14 (11): R123. doi:10.1186/gb-2013-14-11-r123. PMC 4053976. PMID 24200126.
  18. Emerson JB, Roux S, Brum JR, Bolduc B, Woodcroft BJ, Jang HB, et al. (August 2018). "Host-linked soil viral ecology along a permafrost thaw gradient". Nature Microbiology. 3 (8): 870–880. doi:10.1038/s41564-018-0190-y. PMC 6786970. PMID 30013236.
  19. Goericke R, Welschmeyer NA (1993-11-01). "The marine prochlorophyte Prochlorococcus contributes significantly to phytoplankton biomass and primary production in the Sargasso Sea". Deep Sea Research Part I: Oceanographic Research Papers. 40 (11): 2283–2294. Bibcode:1993DSRI...40.2283G. doi:10.1016/0967-0637(93)90104-B. ISSN 0967-0637.
  20. ^ Shaffer M, Borton MA, McGivern BB, Zayed AA, La Rosa SL, Solden LM, et al. (September 2020). "DRAM for distilling microbial metabolism to automate the curation of microbiome function". Nucleic Acids Research. 48 (16): 8883–8900. doi:10.1093/nar/gkaa621. PMC 7498326. PMID 32766782.
  21. Pratama AA, Bolduc B, Zayed AA, Zhong ZP, Guo J, Vik DR, et al. (2021-06-14). "Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation". PeerJ. 9: e11447. doi:10.7717/peerj.11447. PMC 8210812. PMID 34178438.
  22. ^ Kieft K, Zhou Z, Anantharaman K (June 2020). "VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences". Microbiome. 8 (1): 90. doi:10.1186/s40168-020-00867-0. PMC 7288430. PMID 32522236.
  23. Forterre P, Soler N, Krupovic M, Marguet E, Ackermann HW (January 2013). "Fake virus particles generated by fluorescence microscopy". Trends in Microbiology. 21 (1): 1–5. doi:10.1016/j.tim.2012.10.005. PMID 23140888.
  24. Soler N, Krupovic M, Marguet E, Forterre P (March 2015). "Membrane vesicles in natural environments: a major challenge in viral ecology". The ISME Journal. 9 (4): 793–796. Bibcode:2015ISMEJ...9..793S. doi:10.1038/ismej.2014.184. PMC 4817693. PMID 25314322.
  25. Zolfo M, Pinto F, Asnicar F, Manghi P, Tett A, Bushman FD, Segata N (December 2019). "Detecting contamination in viromes using ViromeQC". Nature Biotechnology. 37 (12): 1408–1412. doi:10.1038/s41587-019-0334-5. hdl:11572/246053. PMID 31748692. S2CID 208191024.
  26. Guo J, Bolduc B, Zayed AA, Varsani A, Dominguez-Huerta G, Delmont TO, et al. (February 2021). "VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses". Microbiome. 9 (1): 37. doi:10.1186/s40168-020-00990-y. PMC 7852108. PMID 33522966.
  27. Ren J, Song K, Deng C, Ahlgren NA, Fuhrman JA, Li Y, et al. (March 2020). "Identifying viruses from metagenomic data using deep learning". Quantitative Biology. 8 (1): 64–77. doi:10.1007/s40484-019-0187-4. PMC 8172088. PMID 34084563.
  28. Nayfach S, Camargo AP, Schulz F, Eloe-Fadrosh E, Roux S, Kyrpides NC (May 2021). "CheckV assesses the quality and completeness of metagenome-assembled viral genomes". Nature Biotechnology. 39 (5): 578–585. doi:10.1038/s41587-020-00774-7. PMC 8116208. PMID 33349699.
  29. ^ Crummett LT, Puxty RJ, Weihe C, Marston MF, Martiny JB (December 2016). "The genomic content and context of auxiliary metabolic genes in marine cyanomyoviruses". Virology. 499: 219–229. doi:10.1016/j.virol.2016.09.016. PMID 27693926. S2CID 205652754.
  30. Millard AD, Zwirglmaier K, Downey MJ, Mann NH, Scanlan DJ (September 2009). "Comparative genomics of marine cyanomyoviruses reveals the widespread occurrence of Synechococcus host genes localized to a hyperplastic region: implications for mechanisms of cyanophage evolution". Environmental Microbiology. 11 (9): 2370–2387. Bibcode:2009EnvMi..11.2370M. doi:10.1111/j.1462-2920.2009.01966.x. PMID 19508343.
  31. Darling AC, Mau B, Blattner FR, Perna NT (July 2004). "Mauve: multiple alignment of conserved genomic sequence with rearrangements". Genome Research. 14 (7): 1394–1403. doi:10.1101/gr.2289704. PMC 442156. PMID 15231754.
  32. Li Y, Xiong L, Yu H, Xiang Y, Wei Y, Zhang Q, Ji X (March 2023). "Biogeochemical sulfur cycling of virus auxiliary metabolic genes involved in Napahai plateau wetland". Environmental Science and Pollution Research International. 30 (15): 44430–44438. Bibcode:2023ESPR...3044430L. doi:10.1007/s11356-023-25408-8. PMID 36692711. S2CID 256192280.
  33. Zimmerman AE, Howard-Varona C, Needham DM, John SG, Worden AZ, Sullivan MB, et al. (January 2020). "Metabolic and biogeochemical consequences of viral infection in aquatic ecosystems". Nature Reviews. Microbiology. 18 (1): 21–34. doi:10.1038/s41579-019-0270-x. PMID 31690825. S2CID 207894289.
  34. Anantharaman K, Duhaime MB, Breier JA, Wendt KA, Toner BM, Dick GJ (May 2014). "Sulfur oxidation genes in diverse deep-sea viruses". Science. 344 (6185): 757–760. Bibcode:2014Sci...344..757A. doi:10.1126/science.1252229. hdl:1912/6700. PMID 24789974. S2CID 692770.
  35. Rohwer F, Thurber RV (May 2009). "Viruses manipulate the marine environment". Nature. 459 (7244): 207–212. Bibcode:2009Natur.459..207R. doi:10.1038/nature08060. PMID 19444207. S2CID 4397295.
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