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1. Harnessing machine learning and synthetic microbial communities to control harmful algal blooms

   https://doi.org/10.1016/j.teengi.2025.100030  

   Imam_ul_Khabir, Md; Alam, Nur E; Jhumur, JF; Rehman, Tanzeel U; Jain, Sapna; Rahman, MA; Zhao, Yongpo; Saleem, Muhammad (September 2025, Total Environment Engineering)

   Freshwater with high quality is crucial for both public health and aquatic biodiversity. However, freshwater resources face numerous challenges, including the proliferation of harmful algal blooms (HABs) caused by various cyanobacterial species that are generally triggered by human activities like agricultural runoff and wastewater. Native algicidal microbiomes may offer potential solutions, although challenges remain in utilizing microbial resources to mitigate HABs in freshwater environments. The combination of synthetic microbial community and probiotic development approaches with robust machine learning tools could allow us to harness native microbiomes to address water quality issues caused by HABs in large water bodies. A meta-analysis of around 100 research studies regarding algicidal bacteria-algae interactions was conducted to quantitatively assess the potential of taxonomically diverse microbial species in controlling HABs in freshwater ecosystems. Meta-analysis findings revealed that diverse species from common freshwater bacterial phyla such as Actinobacteria, Bacteroidota, Firmicutes, and Proteobacteria exhibited 50100 % algicidal activity against different algal species depending on interacting species and environmental conditions. Algicidal taxa (mainly against Microcystis aeruginosa) from both Actinobacteria and Firmicutes primarily included Actinomycetes and Bacillus species. However, Bacteroidota and alpha/beta Proteobacteria exhibited algicidal activity against a broader range of algal species, thus highlighting their potential for controlling multi-species HABs in freshwater environments. Based on this quantitative analysis, the current review puts forward synthetic microbial communities and machine-learning based frameworks to develop microbial solutions for protecting freshwater resources from HABs invasions. 

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2. Predicting partner fitness based on spatial structuring in a light-driven microbial community

   https://doi.org/10.1371/journal.pcbi.1011045  

   Sakkos, Jonathan K; Santos-Merino, María; Kokarakis, Emmanuel J; Li, Bowen; Fuentes-Cabrera, Miguel; Zuliani, Paolo; Ducat, Daniel C (May 2023, PLOS Computational Biology)

   Mendes, Pedro (Ed.)

   Microbial communities have vital roles in systems essential to human health and agriculture, such as gut and soil microbiomes, and there is growing interest in engineering designer consortia for applications in biotechnology (e.g., personalized probiotics, bioproduction of high-value products, biosensing). The capacity to monitor and model metabolite exchange in dynamic microbial consortia can provide foundational information important to understand the community level behaviors that emerge, a requirement for building novel consortia. Where experimental approaches for monitoring metabolic exchange are technologically challenging, computational tools can enable greater access to the fate of both chemicals and microbes within a consortium. In this study, we developed anin-silicomodel of a synthetic microbial consortia of sucrose-secretingSynechococcus elongatusPCC 7942 andEscherichia coliW. Our model was built on the NUFEB framework for Individual-based Modeling (IbM) and optimized for biological accuracy using experimental data. We showed that the relative level of sucrose secretion regulates not only the steady-state support for heterotrophic biomass, but also the temporal dynamics of consortia growth. In order to determine the importance of spatial organization within the consortium, we fit a regression model to spatial data and used it to accurately predict colony fitness. We found that some of the critical parameters for fitness prediction were inter-colony distance, initial biomass, induction level, and distance from the center of the simulation volume. We anticipate that the synergy between experimental and computational approaches will improve our ability to design consortia with novel function. 

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3. Long-duration environmental biosensing by recording analyte detection in DNA using recombinase memory

   https://doi.org/10.1128/aem.02363-23  

   Kalvapalle, Prashant Bharadwaj; Sridhar, Swetha; Silberg, Jonathan J; Stadler, Lauren B (April 2024, Applied and Environmental Microbiology)

   Rudi, Knut (Ed.)

   ABSTRACT Microbial biosensors that convert environmental information into real-time visual outputs are limited in their sensing abilities in complex environments, such as soil and wastewater, due to optical inaccessibility. Biosensors that could record transient exposure to analytes within a large time window for later retrieval represent a promising approach to solve the accessibility problem. Here, we test the performance of recombinase-memory biosensors that sense a sugar (arabinose) and a microbial communication molecule (3-oxo-C12-L-homoserine lactone) over 8 days (~70 generations) following analyte exposure. These biosensors sense the analyte and trigger the expression of a recombinase enzyme which flips a segment of DNA, creating a genetic memory, and initiates fluorescent protein expression. The initial designs failed over time due to unintended DNA flipping in the absence of the analyte and loss of the flipped state after exposure to the analyte. Biosensor performance was improved by decreasing recombinase expression, removing the fluorescent protein output, and using quantitative PCR to read out stored information. Application of memory biosensors in wastewater isolates achieved memory of analyte exposure in an uncharacterizedPseudomonasisolate. By returning these engineered isolates to their native environments, recombinase-memory systems are expected to enable longer duration andin situinvestigation of microbial signaling, cross-feeding, community shifts, and gene transfer beyond the reach of traditional environmental biosensors.IMPORTANCEMicrobes mediate ecological processes over timescales that can far exceed the half-lives of transient metabolites and signals that drive their collective behaviors. We investigated strategies for engineering microbes to stably record their transient exposure to a chemical over many generations through DNA rearrangements. We identify genetic architectures that improve memory biosensor performance and characterize these in wastewater isolates. Memory biosensors are expected to be useful for monitoring cell-cell signals in biofilms, detecting transient exposure to chemical pollutants, and observing microbial cross-feeding through short-lived metabolites within cryptic methane, nitrogen, and sulfur cycling processes. They will also enablein situstudies of microbial responses to ephemeral environmental changes, or other ecological processes that are currently challenging to monitor non-destructively using real-time biosensors and analytical instruments. 

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4. New approaches to secondary metabolite discovery from anaerobic gut microbes

   https://doi.org/10.1007/s00253-024-13393-y  

   Butkovich, Lazarina_V; Vining, Oliver_B; O’Malley, Michelle_A (January 2025, Applied Microbiology and Biotechnology)

   AbstractThe animal gut microbiome is a complex system of diverse, predominantly anaerobic microbiota with secondary metabolite potential. These metabolites likely play roles in shaping microbial community membership and influencing animal host health. As such, novel secondary metabolites from gut microbes hold significant biotechnological and therapeutic interest. Despite their potential, gut microbes are largely untapped for secondary metabolites, with gut fungi and obligate anaerobes being particularly under-explored. To advance understanding of these metabolites, culture-based and (meta)genome-based approaches are essential. Culture-based approaches enable isolation, cultivation, and direct study of gut microbes, and (meta)genome-based approaches utilizeinsilicotools to mine biosynthetic gene clusters (BGCs) from microbes that have not yet been successfully cultured. In this mini-review, we highlight recent innovations in this area, including anaerobic biofoundries like ExFAB, the NSF BioFoundry for Extreme & Exceptional Fungi, Archaea, and Bacteria. These facilities enable high-throughput workflows to study oxygen-sensitive microbes and biosynthetic machinery. Such recent advances promise to improve our understanding of the gut microbiome and its secondary metabolism. Key points• Gut microbial secondary metabolites have therapeutic and biotechnological potential• Culture- and (meta)genome-based workflows drive gut anaerobe metabolite discovery• Anaerobic biofoundries enable high-throughput workflows for metabolite discovery Graphical abstract 

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5. Gut microbiota of ring-tailed lemurs (Lemur catta) vary across natural and captive populations and correlate with environmental microbiota

   https://doi.org/10.1186/s42523-022-00176-x  

   Bornbusch, Sally L.; Greene, Lydia K.; Rahobilalaina, Sylvia; Calkins, Samantha; Rothman, Ryan S.; Clarke, Tara A.; LaFleur, Marni; Drea, Christine M. (April 2022, Animal Microbiome)

   Abstract BackgroundInter-population variation in host-associated microbiota reflects differences in the hosts’ environments, but this characterization is typically based on studies comparing few populations. The diversity of natural habitats and captivity conditions occupied by any given host species has not been captured in these comparisons. Moreover, intraspecific variation in gut microbiota, generally attributed to diet, may also stem from differential acquisition of environmental microbes—an understudied mechanism by which host microbiomes are directly shaped by environmental microbes. To more comprehensively characterize gut microbiota in an ecologically flexible host, the ring-tailed lemur (Lemur catta; n = 209), while also investigating the role of environmental acquisition, we used 16S rRNA sequencing of lemur gut and soil microbiota sampled from up to 13 settings, eight in the wilderness of Madagascar and five in captivity in Madagascar or the U.S. Based on matched fecal and soil samples, we used microbial source tracking to examine covariation between the two types of consortia. ResultsThe diversity of lemur gut microbes varied markedly within and between settings. Microbial diversity was not consistently greater in wild than in captive lemurs, indicating that this metric is not necessarily an indicator of host habitat or environmental condition. Variation in microbial composition was inconsistent both with a single, representative gut community for wild conspecifics and with a universal ‘signal of captivity’ that homogenizes the gut consortia of captive animals. Despite the similar, commercial diets of captive lemurs on both continents, lemur gut microbiomes within Madagascar were compositionally most similar, suggesting that non-dietary factors govern some of the variability. In particular, soil microbial communities varied across geographic locations, with the few samples from different continents being the most distinct, and there was significant and context-specific covariation between gut and soil microbiota. ConclusionsAs one of the broadest, single-species investigations of primate microbiota, our study highlights that gut consortia are sensitive to multiple scales of environmental differences. This finding begs a reevaluation of the simple ‘captive vs. wild’ dichotomy. Beyond the important implications for animal care, health, and conservation, our finding that environmental acquisition may mediate aspects of host-associated consortia further expands the framework for how host-associated and environmental microbes interact across different microbial landscapes. 

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