Adaptation of Enterococcus faecalis to intestinal mucus revealed by a human colonic organoid model | mSystems Gut microbiota interactions with mucus during early intestinal colonization are critical for establishing stable communities and influencing host health. Using human colonic organoids combined with Tn-seq and live imaging, this study reveals how Enterococcus faecalis adapts to the mucosal surface by forming microcolonies and reprogramming its metabolism. This integrative approach provides a powerful platform to study other microbiota members in the native-like environment of the large intestine and evaluate potential therapeutic interventions.

Adaptation of Enterococcus faecalis to intestinal mucus revealed by a human colonic organoid model

#mSystems from Alexandre Persat
with @kimingeneva.bsky.social

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Multi-omics identification of molecular signatures of S. aureus adaptation to serum.

Metabolic versatility in carbon source usage, iron transport and resistance to oxidative stress is interlinked and central to S. aureus fitness in serum, representing potential S. aureus vulnerabilities that could be exploited therapeutically. #mSystems; asm.social/2Q8

Salt supplementation-induced metabolic reprogramming in Streptomyces coelicolor | mSystems Precise control of cellular metabolism is critical to ensure directing cellular resources toward metabolic pathways required for the environment. Many Streptomyces species activate production of secon...

Salt supplementation-induced metabolic reprogramming in Streptomyces coelicolor

#mSystems from @nmouncey.bsky.social

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Paenitracins, a novel family of bacitracin-type nonribosomal peptide antibiotics produced by plant-associated Paenibacillus species | mSystems Members of the genus Paenibacillus play an important role in soil ecology, producing a range of important nonribosomal peptides (NRPs). A collection of plant-associated Paenibacillus spp. were analyzed for their phylogenetic and metabolic diversity. We developed a novel discovery pipeline that combines feature-based molecular networking with mass spectrometry query language queries to systematically prioritize bioactive NRPs containing basic amino acids. Thus, we provide a comprehensive genus-wide inventory of NRPs produced by Paenibacillus spp. We thereby identified the paenitracins, a new sub-family of bacitracins active against multidrug-resistant gram-positive pathogens. Our pipeline enables the discovery of novel peptidic natural products to accelerate the prioritization of chemical space for antibiotics.

Paenitracins, a novel family of bacitracin-type nonribosomal peptide antibiotics produced by plant-associated Paenibacillus species
MassQL on 227 plant-associated Paenibacillus

#mSystems by Nataliia Machushynets et al from @gillesvanwezel.bsky.social #LeidenBiology

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Han Solo Bacteria How Desert Microbes Freeze Themselves in Time

New UnCultured post is a "behind the paper" about our new editor's pick in the #mSystems Dormancy Special Collection. Started pre-pandemic—challenging times for studying persistence—fitting, right?

uncultured.carinilab.com/p/when-bacte...
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On the surface of aging washed-rind cheeses (photo on left), A. westerdijkiae causes the typical orange rind to be discolored and sometimes develop wrinkles. In simulated cheese rinds in the lab, the same wrinkle phenotype appears after 21 days of rind development (photos of plates on right).

#MicrobiologyMonday: The spoilage fungus Aspergillus westerdijkiae inhibits beneficial cheese-rind bacteria via production of penicillic acid. Insights like this can help researchers assess the risks of fungal-driven spoilage in cheese. #mSystems: asm.social/2Ma

Overview of the NIAID data ecosystem interface and example search. (A) The landing page provides access to the Discovery Portal’s basic search interface. (B) Example search results for “Zika virus” data sets filtered by species: “Homo sapiens” and variableMeasured: “Proteomics,” demonstrating how users can refine results using structured metadata filters to support targeted data discovery.

Valuable data sets are often overlooked because they are difficult to locate. The NIAID Data Ecosystem Discovery Portal provides a centralized, searchable interface that empowers users with varying technical expertise to find and reuse data. #mSystems: asm.social/2Lo

Scripps Research scientists published a new #mSystems article describing the @niaidnews.bsky.social Discovery Portal, a metadata-driven platform that enables discovery of infectious and immune-mediated disease datasets. More: ow.ly/iGwC50XSA8G #BiomedicalData #InfectiousDisease

Register Now for the Next mSystems Thinking Series One Health and the African Microbiome Jan. 9, 2026 9 a.m. ET (3 p.m. West Africa Time)

Why does African microbiome research matter worldwide? Find out at the next mSystems Thinking Series webinar:

🌍 One Health & the African Microbiome
🗓 Jan 9 | ⏰ 9 a.m. ET / 3 p.m. WAT
✅ Register for free! asm.social/2KU
#Microbiome #Africa #OneHealth #mSystems

In December’s issue of mSystems, a team led by Laura Rodriguez-Castro Sanchez and Timothy Donohue at the University of Wisconsin-Madison describe how the aromatic-compound-eating alphaproteobacteria Novosphingobium aromaticivorans regulates a complex network for of genes involved in the aromatic compound degradation pathways via the master regulator LigR. 

They also find that this pathway is branched, allowing the bacterium to catabolise structurally different aromatic compounds, and how it uses regulation to orchestrate the activity of the same enzymes involved in different parts of the network. 

This work is relevant to many areas of research such as wood decaying processes in carbon cycle in natural environments (lignin degradation), bioremediation of polluted soils and sediments with petroleum and its derivatives (toluene, benzene, phenol, PHAs), and opens possibilities to bioengineering novel pathways for the degradation and transformation of aromatic compounds.

🦠🧪🔬🧫🌍 Rodriguez-Castro et al describe how 𝑵𝒐𝒗𝒐𝒔𝒑𝒉𝒊𝒏𝒈𝒐𝒃𝒊𝒖𝒎 𝒂𝒓𝒐𝒎𝒂𝒕𝒊𝒄𝒊𝒗𝒐𝒓𝒂𝒏𝒔 coordinates a branched pathway for degrading aromatic compounds via the master regulator LigR, relevant for wood decay and bioremediation of polluted soils!
More in the ALT text and #mSystems journals.asm.org/doi/10.1128/...

Unveiling the landscape of prokaryotic global regulators through deep protein language models | mSystems GRs are master transcriptional regulators critical for microbial adaptation, stress tolerance, and metabolic control, and they serve as valuable components for synthetic biology. However, a comprehens...

Unveiling the landscape of prokaryotic global regulators through deep protein language models

-in #mSystems

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Gempipe: a tool for drafting, curating, and analyzing pan and multi-strain genome-scale metabolic models | mSystems Available genome-scale metabolic model (GSMM) reconstruction tools present major limitations in the context of multi-strain modeling. Gempipe surpasses these limitations by implementing a novel, hybrid reconstruction strategy. Not only does it produce more accurate strain-specific GSMMs, but it also produces pan-GSMMs when the only available reference is a manually curated model for a single strain, which is currently the most common case. With the vast availability of genome sequences, the high-throughput, multi-strain GSMM reconstruction and analysis approach provided by Gempipe will facilitate large-scale studies of exploration and bioprospecting of strain-level bacterial metabolic diversity, moving a step forward in strains’ screening and rational selection.

Gempipe: a tool for drafting, curating, and analyzing pan and multi-strain genome-scale metabolic models

#mSystems from Nicola Vitulo
with @basteusink.bsky.social

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Dormancy and reactivation of the seed and its microbiome: a holobiont perspective

#mSystems review by Davide Gerna, @thomas-chadelaud.bsky.social, @fly-florian.bsky.social, @lmatthieul.bsky.social, Armelle Darrasse and @microbialmarie.bsky.social

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Using cross-species co-expression to predict metabolic interactions in microbiomes | mSystems An improved mechanistic understanding of microbial interactions can guide targeted interventions or inform the rational design of microbial communities to optimize them for applications such as pathog...

Using cross-species co-expression to predict metabolic interactions in microbiomes

#mSystems by Robert Koetsier et al from @marnixmedema.bsky.social and @jjjvanderhooft.bsky.social

with @wildtypemc.bsky.social, Jo Handelsman, Clara Belzer, Yijun Zhu ...

journals.asm.org/doi/10.1128/...

Now out in @asm.org #mSystems! journals.asm.org/doi/10.1128/...
Congratulations to Robert and thanks to all collaborators. See thread below for a summary of the work, exploring the use of cross-species coexpression analyses to predict primary and secondary metabolic interactions in microbiomes.

There is no conservation without microbial conservation: anthropogenic stressors, and loss of microbial diversity drive ecosystem degradation and pathogen proliferation across connected biomes. In absence of diversity and beneficial microbiota, terrestrial, coastal, and marine habitats are increasingly linked by the spread of harmful microorganisms fueled by pollution, habitat destruction, and climate change. Deforestation, agricultural runoff, chemical contamination, and industrial waste disrupt microbial community balance, leading to the replacement of beneficial microbes by pathogenic taxa. These pathogens circulate among ecosystems and hosts, exacerbating biodiversity loss, impairing organism health, and threatening ecosystem services and, ultimately, human health. Some of the figure vectors were designed by macrovector/Freepik.

#MicrobiologyMonday: Save the microbes! 🦠Most conservation frameworks focus on organisms we can see, not the ones we can't. The International Union for Conservation of Nature Microbial Conservation Specialist Group seeks to address this gap: #mSystems: asm.social/2IZ

Register Now for the Next mSystems Thinking Series One Health and the African Microbiome Jan. 9, 2026 9 a.m. ET (3 p.m. West Africa Time)

#mSystems Thinking Series webinar is back!

One Health & the African Microbiome | Jan 9 | 9 a.m. ET / 3 p.m. WAT

Africa’s microbiomes are rich, diverse & important. Learn how One Health research can advance health, food security & climate resilience. asm.social/2Iv

Nutrient limitation shapes functional traits of mycorrhizal fungi and phosphorus-cycling bacteria across an elevation gradient | mSystems Phosphorus (P) limits plant productivity in high-elevation ecosystems, yet the microbial networks that mobilize P, including arbuscular mycorrhizal (AM) fungi and phosphorus-cycling bacteria (PCBs), remain under-characterized in these nutrient-poor soils. We show that across a 10,00-m elevation gradient, AM fungi and P-cycling gene assemblages shift predictably with pH, organic carbon, and phosphate availability. Higher elevations, with less available P, select for stress-tolerant AM fungal taxa and PCB strategies geared toward mineral solubilization, while low-elevation sites favor root colonization by AM fungi and organic P mineralization. These results suggest that nutrient limitation can constrain microbial community assembly in consistent ways across landscapes. High mountain soils are low in P and rely on a network of underground AM fungi and PCB to deliver nutrients to plants. This study shows how those underground relationships reorganize with elevation and how climate change could collapse long-standing microbial strategies by pushing high-elevation ecosystems toward lowland conditions. As soils warm and dry, the microbial scaffolding that supports alpine plant life may become increasingly unstable.

Nutrient limitation shapes functional traits of mycorrhizal fungi and phosphorus-cycling bacteria across an elevation gradient

#mSystems by @hannahshulman.bsky.social et al

journals.asm.org/doi/10.1128/...

Virtual Colon: spatiotemporal modeling of metabolic interactions in a computational colonic environment | mSystems Interactions between the human body and gut microbes are crucial for health and disease. We present the Virtual Colon, an extension of the individual-based microbiome modeling approach BacArena that m...

Virtual Colon: spatiotemporal modeling of metabolic interactions in a computational colonic environment

#mSystems from @kaletalab.bsky.social

journals.asm.org/doi/10.1128/...

The infection cycle of the haloarchaeal virus HFTV1 is tightly regulated and strongly inhibits motility of its host | mSystems Viruses infect members of all three domains of life, including Archaea. Euryarchaea are widespread microorganisms found in various environments, such as the human gut and solar salterns. Due to the ex...

Leonard starts on using the RNAseq data published by the group in #mSystems recently on HFTV1 infection of archaeal cells
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#HMG2025

Strain matters: host responses reflect symbiont origin in the squid-vibrio symbiosis | mSystems Variation among strains of a bacterial species is a powerful factor underlying the intensity of host responses during pathogenic infections. Less is known about the cellular and molecular responses of...

Strain matters: host responses reflect symbiont origin in the squid-vibrio symbiosis

in #mSystems from Margaret McFall-Ngai

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Time-series RNA metabarcoding of the active Populus tremuloides root microbiome reveals hidden temporal dynamics and dormant core members

#mSystems by @jakenash12.bsky.social et al

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Metabolite Production in Alkanna tinctoria Links Plant Development with the Recruitment of Individual Members of Microbiome Thriving at the Root-Soil Interface | mSystems Previous studies have shown that individual, isolated microorganisms may influence secondary metabolism of plants and induce or stimulate the production of medicinally relevant secondary metabolism. H...

Angela on their story for microbiome and plant secondary metabolite production in Alkanna tinctoria
See in #mSystems:
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#PMS2025

Spatially divergent metabolic impact of experimental toxoplasmosis: immunological and microbial correlates | mSystems Inflammation is a major driver of tissue perturbation. However, the signals driving these changes on a tissue-intrinsic and molecular level are poorly understood. This study evaluated tissue-specific ...

Spatially divergent metabolic impact of experimental toxoplasmosis: immunological and microbial correlates #mSystems #MassSpec journals.asm.org/doi/10.1128/...

Metabolic profiles of PA-RGEN.

Exogenous glutamate restores gentamicin efficacy against antibiotic-resistant P. aeruginosa by reprogramming bacterial metabolism to enhance membrane permeability. The effect is mediated through increased biosynthesis of unsaturated fatty acids. #mSystems: asm.social/2Ez

Exo-metabolome profiling of soybean endophytes: a road map of antagonism against Fusarium oxysporum | mSystems Modern agricultural practices depend heavily on synthetic fertilizers and pesticides, which are major contributors to greenhouse gas emissions, groundwater pollution, and disruptions in agroecosystem ...

Exo-metabolome profiling of soybean endophytes: a road map of antagonism against Fusarium oxysporum #mSystems #MassSpec journals.asm.org/doi/10.1128/...

Tracking clonal and plasmid transmission in colistin- and carbapenem-resistant Klebsiella pneumoniae | mSystems Antimicrobial resistance occupies a central stage in global public health emergencies. Recently, efforts to track the genetic elements that facilitate the spread of resistance genes in plasmids outbreaks, utilizing short-read sequencing technologies, have ...

Some of her findings were recently published in #mSystems
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Integrated diversity and network analyses reveal drivers of microbiome dynamics | mSystems Understanding microbiome dynamics requires capturing not only changes in microbial composition but also interactions between community members. Traditional approaches frequently overlook microbe-micro...

Integrated diversity and network analyses reveal drivers of microbiome dynamics

#mSystems by @guan06rui.bsky.social and Ruben Garrido-Oter

journals.asm.org/doi/10.1128/...

Use of the CHM13-T2T genome improves metagenomic analysis by minimizing host DNA contamination. #MetagenomicAnalysis #HostDNA #CHM13T2T #ReferenceGenome #mSystems
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