Biology subjects

Wolfram, M.

Publications and source records attributed to Wolfram, M..

3 recordsLinked to original sources

bioRxiv2025

Single-cell mass accumulation reveals bacterioplankton growth rate in native seawater

AO_SCPLOWBSTRACTC_SCPLOWThe growth of marine microbial communities drives biogeochemical cycling of carbon and other elements, yet the growth rates of individual species within complex ocean ecosystems remain poorly understood. In particular, the coexistence of a large diversity of copiotrophic bacteria, which are capable of fast growth but typically remain at low abundance, has been interpreted as a feast or famine existence. Here we show that contrary to the notion of infrequent growth, Vibrio bacteria exhibited consistent growth rates in coastal ocean samples, despite representing only a small fraction of the total community. These observations were enabled by a suspended microchannel resonator (SMR), which we adapted to function as a single-cell chemostat. By maintaining a continuous supply of native seawater around each trapped cell, we prevented nutrient depletion and used the SMRs high mass precision to resolve growth rates that are otherwise undetectable. Vibrio species displayed significantly larger cell mass and faster growth than other community members across samples collected at different temporal intervals from days to years. Surprisingly, their growth was consistently limited by carbon, contrary to the expectation that heterotrophic bacteria in the euphotic zone would be limited by nitrogen and phosphorus due to competition with algae. The correlation between cell mass and growth rate of Vibrionaceae in seawater followed established growth laws derived from laboratory conditions, suggesting that growth physiology observed in pure cultures is applicable to wild bacterial populations. Overall, our findings suggest that rare species may play a disproportionately large role in the marine carbon cycle, with rapid biomass turnover driven by a combination of high growth rates balanced by intense predation.

microbiology↗

bioRxiv2025

Bacterial peptide deformylase inhibitors induce prophages in competitors

While antibiotics mediate chemical warfare among microbes, their roles in the wild extend beyond direct growth inhibition(1). Some antibiotics have the potential to mediate interference competition by triggering a bacterial stress response that subsequently activates endogenous viruses integrated in bacterial genomes (prophages). Canonically, this activation is regulated by the SOS response upon DNA damage. Here we show that a metabolite produced by natural isolates of Vibrio ordalii circumvents the SOS response by directly triggering prophage induction in other Vibrio species, co-occurring in the same environment. While the metabolite was previously classified as a broad-spectrum antibiotic, we observe how it acts as a peptide deformylase inhibitor that specifically induces certain prophages, even when target bacterial cells carry multiple other prophages. Its biosynthetic gene cluster, or ord cluster, also encodes its own peptide deformylase (OrdE) which provides self-immunity to producer strains. Likewise, among natural Vibrio isolates that carry similar prophages, resistance against the ord metabolite was found in those that had acquired a divergent second peptide deformylase. Finally, we show that prophage induction by the ord cluster prevents slower-growing producer strains from being outcompeted by their otherwise fast-growing competitors if they carry an inducible prophage. Thus, we demonstrate how natural products play additional impactful roles in communities beyond antibiotic activity and that prophage induction serves as an interference competition strategy, sustaining community diversity.

microbiology↗

bioRxiv2024

Interpretable machine learning reveals a diverse arsenal of anti-defenses in bacterial viruses

Antagonistic interactions with viruses are an important driver of the ecology and evolution of bacteria, and associating genetic signatures to these interactions is of fundamental importance to predict viral infection success. Recent studies have highlighted that bacteria possess a large, rapidly changing arsenal of defense genes and that viruses can neutralize at least some of these genes with matching anti-defenses. However, a broadly applicable approach for discovering the genetic underpinnings of such interactions is missing since typically used methods such as comparative genomics are limited by the rampant horizontal gene transfer and poor annotation of viral and bacterial genes. Here we show that genes that allow the viruses to overcome bacterial defenses can be systematically identified using an interpretable machine-learning approach even when using diverse bacteria-virus infection data. To verify the predictions, we experimentally characterized eight previously unknown anti-defense proteins in viruses specific for Vibrio bacteria and showed that they counteract a wide range of bacterial immune systems, including AbiH, AbiU, Septu, DRT, CBASS, and Retron. The power of our computational approach is highlighted by the identification of anti-defense proteins that inhibit non-homologous defense systems, which we verify for Retron and AbiH. We suggest that the computational prediction based on experimental interactions offers a promising avenue to unravel the genetic mechanisms of co-evolution between bacteria and their viruses.

microbiology↗