Whether and how root exudates of Amorpha fruticosa Linn. mediate the positive effects of microbial inoculation (Bacillus thuringiensis NL-11 and Gongronella butleri NL-15) on soil aggregation remains unclear. We conducted two glasshouse experiments and a controlled laboratory incubation experiment to address this knowledge gap. Glasshouse experiments showed that microbial inoculation increased root exudation, changed soil microbial community structure, and enhanced soil aggregation and mean weight diameter (MWD). Microbial inoculation increased the number of nodes and links in bacterial–fungal exudate association networks across soil aggregate sizes. Network properties, including the number of nodes, total links, and microbial–exudate (ME) links, were positively correlated with soil MWD and mineral-associated organic carbon (MAOC). Partial least squares path modeling revealed that inoculation indirectly increases MWD by enhancing MAOC, which subsequently strengthens ME links. The laboratory incubation experiment further showed that a single addition of inoculation-induced exudates did not promote macroaggregate formation but significantly increased MAOC content relative to the control. Inoculation-induced root exudates increased the number of nodes and links in bacterial–fungal association networks across all aggregate sizes, and these network attributes were positively correlated with MAOC. We demonstrate that microbial inoculation enhances soil aggregation and carbon stabilization through root exudate-mediated microbial association networks.

Cable bacteria are filamentous sulphide-oxidizing bacteria that transport electrons through conductive periplasmic fibres over centimetre-scale distances in redox-stratified sediments to respire oxygen. Here, we show that the freshwater cable bacterium Electronema aureum GS employs a versatile extracellular electron transfer (EET) system to respire insoluble electron acceptors under anoxic conditions, achieving growth rates comparable to aerobic respiration. Electrochemical and molecular analyses reveal that E. aureum GS performs both direct and riboflavin-mediated EET to electrodes, including at +600 mV vs. Ag/AgCl, an unusually high redox potential typically not accessed by electroactive bacteria. Two distinct cell-surface redox components were identified, which are metal-dependent, pH-sensitive, and heat-labile, consistent with outer-membrane-localized cytochromes. The redox shuttle riboflavin accumulated in bioelectrochemical systems with E. aureum GS, supporting mediated EET. These findings reveal a respiratory flexibility in E. aureum GS and highlight the role of EET in energy conservation in dynamic redox environments. In this study, the authors show that cable bacteria perform extracellular electron transfer via direct and flavin-mediated pathways, which enables growth under anoxic conditions at rates comparable to aerobic respiration, revealing their metabolic versatility.

Scientific discovery is driven by scientists generating novel hypotheses for complex problems that undergo rigorous experimental validation. To augment this process, we introduce Co-Scientist, a multi-agent AI system built on Gemini for structured scientific thinking and hypothesis generation. Co-Scientist aims to help scientists discover new original knowledge. Conditioned on their research objectives and prior scientific evidence, it formulates demonstrably novel research hypotheses for experimental verification. The system’s design involves agents continuously generating, critiquing and refining hypotheses accelerated by scaling test-time compute. Key contributions include: (1) a multi-agent architecture with an asynchronous task execution framework for flexible compute scaling; (2) a tournament evolution process for self-improving hypotheses generation. Automated evaluations show continued benefits of test-time compute scaling, improving hypothesis quality over time. While general purpose, we focus the validation in three biomedical applications: drug repurposing, novel target discovery, and explaining mechanisms of anti-microbial resistance. Specifically, Co-Scientist helped identify new drug repurposing candidates and synergistic combination therapies for acute myeloid leukemia, which were validated through in vitro experiments. These real-world validations demonstrate the potential of Co-Scientist to accelerate scientific discovery and usher in an era of AI empowered scientists.

Organic compounds with a negative nominal oxidation state of carbon (NOSC) are thermodynamically recalcitrant in anaerobic ecosystems, but few studies have measured the influence of NOSC on carbon degradation rates, gaseous product yields, or microbiome composition. We amended anaerobic rice paddy sediment microcosms with water-soluble monomeric organic carbon compounds varying in NOSC. Consistent with thermodynamic and stoichiometric predictions, negative NOSC compounds are catabolized more slowly but produce more methane per mole of carbon. Negative NOSC microbiomes have higher alpha diversity, more syntrophs and methanogens, and fewer fermentative bacteria. Strikingly, fermentative bacterial taxa display genomically encoded NOSC catabolic preferences both in the lab and field. Negative NOSC-preferring fermenters have longer predicted doubling times, consistent with the thermodynamic recalcitrance of their preferred substrates. We propose that microbial NOSC catabolic preferences may reflect the thermodynamic niche of microorganisms and we anticipate that extending research on microbial catabolic preferences to a greater variety of organic carbon substrates and diverse microbiomes will improve our understanding of microbial carbon cycling and trait evolution. Microbial methanogenesis is responsible for ~70% of global methane emissions. Here, the authors show that negative nominal oxidation state of carbon (NOSC) compounds are catabolized more slowly but produce more methane per mole of carbon and that NOSC impacts microbial community composition in microcosms.

In Pseudomonas umsongensis GO16, a LysR-type transcriptional regulator (LTTRs) ttdR is located 5′ of the gene for glyoxylate carboligase (gcl), involved in ethylene glycol (EG) metabolism. GO16 wildtype (WT) can utilize EG as a sole carbon and energy source but the ttdR knockout strain (ΔttdR) cannot grow on EG, demonstrating its role as an activator in EG metabolism. When ΔttdR was grown with terephthalic acid (TA) or glucose, the growth was comparable to the WT. GO16 originally produces both C4 short-chain-length (scl) PHA and C6-C12 medium-chain-length (mcl) PHA from various carbon sources. Interestingly, ΔttdR produced scl-PHA monomer 5.4-fold and 1.4-fold increased than the WT when TA and glucose were used respectively. Furthermore, ΔttdR exhibited a very long lag phase when grown with fatty acids, namely butyrate or octanoate. This indicates a more complex role of TtdR than simply activating EG metabolism in GO16. The analysis of the GO16 ΔttdR proteome revealed that EG catabolic genes were expressed, but their abundance was 2.8- to 10.5-fold lower (log2) compared to the WT. In addition, higher abundance of enzymes that could be contributing to higher scl-PHA content was also observed. GO16 ΔttdR was further subjected to adaptive laboratory evolution (ALE) with butyrate and octanoate. The evolved strains regained the ability to grow with these fatty acids as the WT, but the mutations accumulated did not confer growth with EG or acetate, suggesting that a mechanism different to glyoxylate shunt has evolved to allow growth with fatty acids.

De novo peptide sequencing directly infers sequences from mass spectrometry data without relying on protein databases. Although recent deep learning models can also identify posttranslational modifications (PTMs), they require labeled training data for this task. Here we introduce rotary positional embedding-enhanced de novo sequencing algorithm (RNovA), a transformer-based de novo sequencing algorithm enhanced with relative positional embeddings and a reinforcement-learning-style sequential decision framework. RNovA enables open PTM discovery in a zero-shot setting—without retraining or a predefined list of candidate residues—while maintaining state-of-the-art performance on standard benchmarks. Demonstrating this capability, we successfully identified peptides modified by kynurenine—an uncommon and biologically relevant PTM—in clinical samples from patients with RA and validated this discovery with synthetically synthesized reference peptides. Furthermore, we demonstrated open de novo PTM discovery by analyzing the bacterial strain A1232E, which lacks a reference proteome, and detected an unannotated glutamic acid modification. RNovA enables exploration of previously inaccessible regions of the proteome, including peptides with unexpected or unannotated modifications. RNovA is an open-search de novo peptide sequencing model.

Staphylococcus aureus is a major cause of bloodstream infections, but how variation between strains in their ability to adhere to host proteins influences disease severity remains unclear. Here we show that adhesion is a highly variable and biologically important trait in 236 phylogenetically diverse, representative bacteremia isolates profiled for binding to fibrinogen and fibronectin and analysed together with bacterial whole-genome sequences and matched patients’ clinical data. Stronger fibrinogen-binding, particularly in strains lacking α-toxin, correlates with heightened systemic inflammation (r = 0.401, P = 0.0001) but lower mortality (16.6% vs. 38.7%, P = 0.018), linking bacterial adhesion to distinct clinical outcomes. Genome-wide association analyses identify top-associated variants in genes encoding known adhesins (clfA, fnbA, fnbB, ebh), other surface factors (spa, sdrH), mobile genetic elements, and novel loci (csbB, glcA), although not statistically significant. Functional analyses reveal that protein A limits ClfA-dependent fibrinogen binding through steric hindrance, CsbB interferes with ClfA exposure on bacterial surface, and GlcA enhances fibronectin binding via metabolic regulation. These findings define adhesion as a polygenic, evolutionarily variable trait and suggest that highly-adhesive, α-toxin-defective isolates promote inflammatory but self-limiting infections, whereas weakly adhesive, high-toxicity strains favour immune evasion and severe disease. To uncover how Staphylococcus aureus strain variation influences adhesion and thus disease outcomes, the authors profile 236 bacteremia isolates, showing that high-adhesion, low-toxicity isolates may elicit inflammatory yet self-limiting infections.

TALEs (transcription activator-like effectors) are an excellent example of how studying pathogen–host interactions can lead to significant biotechnology inventions. TALEs are bacterial effectors that are translocated into plant cells via a bacterial type III secretion system. Once inside the host cell, they are imported into the nucleus to bind specific promoters and induce expression of target genes, thereby supporting the bacterial infection. TALEs are found throughout many, but not all, Xanthomonas pathovars, which can be severe pathogens of different crops. The key feature of TALEs is their modular DNA-binding domain, which allows a simple evolutionary adaptation to novel DNA sequences as well as simple cloning of designer TALEs with desired DNA-binding specificity. Accordingly, TALE-nucleases started the genome-editing revolution, and TALE base editors are the latest tools to efficiently edit chloroplast and mitochondrial genomes. We review recent advances in Xanthomonas genomics, synthesize current knowledge about naturally occurring TALEs, and highlight current roles of TALEs in genome editing and synthetic biology.

Bacteria dominate the biosphere and assemble into highly diverse communities, yet the mechanisms by which these communities migrate remain poorly understood. Here, we used a meso-tube chemotaxis assay to track taxonomic, functional and genomic shifts within sewage-derived microbial communities that migrate in self-organized bands over metre scales. Chemotactic bands accelerated during migration and incorporated non-motile bacterial hitchhikers as well as up to 10⁶ viruses/mL. Approximately 500 species co-migrated, with relative abundances fluctuating by orders of magnitude over time. The final communities exhibited enrichment of functional genes linked to motility and chemotaxis, consistent with adaptation to migration. Despite this functional convergence, replicate communities differed in taxonomic composition, reflecting environmental filtering that selects for functionally equivalent species. By revealing how chemotaxis governs large-scale microbial migration, this work provides a framework for understanding microbial spread in natural ecosystems and host-associated environments. Migration of microbial communities is poorly understood. Here, the authors use a meso-tube assay to show that hundreds of microbial species co-migrate over metre scales via chemotaxis, which restructures communities, enriches motility traits and facilitates dispersal of viruses and non-motile ‘hitchhikers’.

Microbes, as the planet’s most abundant and diverse organisms, drive soil functions globally and are vulnerable to environmental stressors triggered by global change. Yet, knowledge regarding the impacts of multiple environmental stressors on their functional profiles as well as the consequences for soil functionality largely remains unknown. Here, we analyze two global-scale datasets including information on soil metagenomics and multiple environmental stressors. We find that across terrestrial ecosystems worldwide, up to 60% of all functional genes significantly shift when soil microbes experience the high-level of concurrent stressors. In this regard, the relative abundances of genes involved in microbial growth are negatively linked to the increasing number of stressors. Conversely, those genes linked to stress resistance and energy production exhibit positive responses. Taken together, our findings highlight a significant restructuring of global soil functional microbiomes in response to multiple environmental stressors. Consequently, such restructuring drives community-level shifts in matter and energy reallocations, thereby impacting the maintenance of soil functionality under the projected global change. Soil microbes drive ecosystem functions but are vulnerable to environmental stressors triggered by global change. This study reveals that multiple environmental stressors drive community-level restructuring of soil functional microbiomes globally.

Plants decode environmental light cues through photoreceptors to orchestrate growth and developmental programs. Upon photon absorption, photoreceptor proteins transition from non-photoexcited to photoexcited states, with most functional studies focusing on the activities of the photoexcited form. However, emerging evidence reveals that non-photoexcited photoreceptors exert distinct biological functions in darkness, suggesting unexpected complexity in photon-mediated signalling. In this Perspective, we enumerate current observations underpinning photoreceptor-mediated control of plant development in darkness, categorize mechanisms of photon-dependent modulation and propose an expanded conceptual model that integrates both photoexcited and non-photoexcited activities. These insights reassess the previously overlooked importance of darkness, redefining light and darkness as dynamic, multidimensional regulators of plant physiology. In a manner distinct from their light-activated canonical roles, non-photoexcited photoreceptors can also exert biological functions in darkness, suggesting unexpected complexity in photon-mediated signalling.