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Viruses infect and kill prokaryotic populations in a density- or frequency-dependent manner and affect carbon cycling. However, the effects of the stratification transition, including the stratified and de-stratified periods, on the changes in prokaryotic and viral communities and their interactions remain unclear. We conducted a monthly survey of the surface and deep layers of a large and deep freshwater lake (Lake Biwa, Japan) for a year and analyzed the prokaryotic production and prokaryotic and viral community composition. Our analysis revealed that, in the surface layer, 19 prokaryotic species, accounting for approximately 40% of the total prokaryotic abundance, could potentially contribute to the majority of prokaryotic production, which is the highest during the summer and is suppressed by viruses. This suggests that a small fraction of prokaryotes and phages were the key infection pairs during the peak period of prokaryotic activity in the freshwater lake. We also found that approximately 50% of the dominant prokaryotic and viral species in the deep layer were present throughout the study period. This suggests that the "kill the winner" model could explain the viral impact on prokaryotes in the surface layer, but other dynamics may be at play in the deep layer. Furthermore, we found that annual vertical mixing could result in a similar rate of community change between the surface and deep layers. These findings may be valuable in understanding how communities and the interaction among them change when freshwater lake stratification is affected by global warming in the future.IMPORTANCEViral infection associated with prokaryotic production occurs in a density- or frequency-dependent manner and regulates the prokaryotic community. Stratification transition and annual vertical mixing in freshwater lakes are known to affect the prokaryotic community and the interaction between prokaryotes and viruses. By pairing measurements of virome analysis and prokaryotic production of a 1-year survey of the depths of surface and deep layers, we revealed (i) the prokaryotic infection pairs associated with prokaryotic production and (ii) the reset in prokaryotic and viral communities through annual vertical mixing in a freshwater lake. Our results provide a basis for future work into changes in stratification that may impact the biogeochemical cycling in freshwater lakes., Competing Interests: The authors declare no conflict of interest.

Toxin-antitoxin (TA) modules are prevalent in prokaryotic genomes, often in substantial numbers. For instance, the Mycobacterium tuberculosis genome alone harbors close to 100 TA modules, half of which belong to a singular type. Traditionally ascribed multiple biological roles, recent insights challenge these notions and instead indicate a predominant function in phage defense. TAs are often located within Defense Islands, genomic regions that encode various defense systems. The analysis of genes within Defense Islands has unveiled a wide array of systems, including TAs that serve in anti-phage defense. Prokaryotic cells are equipped with anti-phage Viperins that, analogous to their mammalian counterparts, inhibit viral RNA transcription. Additionally, bacterial Structural Maintenance of Chromosome (SMC) proteins combat plasmid intrusion by recognizing foreign DNA signatures. This study undertakes a comprehensive bioinformatics analysis of genetic elements encoding the HicA double-stranded RNA-binding domain, complemented by protein structure modeling. The HicA toxin domains are found in at least 14 distinct contexts and thus exhibit a remarkable genetic diversity. Traditional bicistronic TA operons represent eight of these contexts, while four are characterized by monocistronic operons encoding fused HicA domains. Two contexts involve hicA adjacent to genes that encode bacterial Viperins. Notably, genes encoding RelE toxins are also adjacent to Viperin genes in some instances. This configuration hints at a synergistic enhancement of Viperin-mediated anti-phage action by HicA and RelE toxins. The discovery of a HicA domain merged with an SMC domain is compelling, prompting further investigation into its potential roles.IMPORTANCEProkaryotic organisms harbor a multitude of toxin-antitoxin (TA) systems, which have long puzzled scientists as "genes in search for a function." Recent scientific advancements have shed light on the primary role of TAs as anti-phage defense mechanisms. To gain an overview of TAs it is important to analyze their genetic contexts that can give hints on function and guide future experimental inquiries. This article describes a thorough bioinformatics examination of genes encoding the HicA toxin domain, revealing its presence in no fewer than 14 unique genetic arrangements. Some configurations notably align with anti-phage activities, underscoring potential roles in microbial immunity. These insights robustly reinforce the hypothesis that HicA toxins are integral components of the prokaryotic anti-phage defense repertoire. The elucidation of these genetic contexts not only advances our understanding of TAs but also contributes to a paradigm shift in how we perceive their functionality within the microbial world., Competing Interests: The author declares no conflict of interest.

CRISPR-Cas systems evolved in prokaryotes to implement a powerful antiviral immune response as a result of sequence-specific targeting by ribonucleoproteins. One of such systems consists of an RNA-guided RNA endonuclease, known as CRISPR-Cas13. In very recent years, this system is being repurposed in different ways in order to decipher and engineer gene expression programmes. Here, we discuss the functional versatility of the CRISPR-Cas13 system, which includes the ability for RNA silencing, RNA editing, RNA tracking, nucleic acid detection and translation regulation. This functional palette makes the CRISPR-Cas13 system a relevant tool in the broad field of systems and synthetic biology., (© 2024 The Authors. Microbial Biotechnology published by Applied Microbiology International and John Wiley & Sons Ltd.)

Toxin-antitoxin systems (TAs) are generally two-component genetic modules present in almost every prokaryotic genome. The production of the free and active toxin is able to disrupt key cellular processes leading to the growth inhibition or death of its host organism in absence of its cognate antitoxin. The functions attributed to TAs rely on this lethal phenotype ranging from mobile genetic elements stabilization to phage defense. Their abundance in prokaryotic genomes as well as their lethal potential make them attractive targets for new antibacterial strategies. The hijacking of TAs requires a deep understanding of their regulation to be able to design such approach. In this review, we summarize the accumulated knowledge on how bacteria cope with these toxic genes in their genome. The characterized TAs can be grouped based on the way they prevent toxicity. Some systems rely on a tight control of the expression to prevent the production of the toxin while others control the activity of the toxin at the post-translational level., (Copyright © 2023 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.)

Viral genomes are poorly annotated in metagenomic samples, representing an obstacle to understanding viral diversity and function. Current annotation approaches rely on alignment-based sequence homology methods, which are limited by the paucity of characterized viral proteins and divergence among viral sequences. Here we show that protein language models can capture prokaryotic viral protein function, enabling new portions of viral sequence space to be assigned biologically meaningful labels. When applied to global ocean virome data, our classifier expanded the annotated fraction of viral protein families by 29%. Among previously unannotated sequences, we highlight the identification of an integrase defining a mobile element in marine picocyanobacteria and a capsid protein that anchors globally widespread viral elements. Furthermore, improved high-level functional annotation provides a means to characterize similarities in genomic organization among diverse viral sequences. Protein language models thus enhance remote homology detection of viral proteins, serving as a useful complement to existing approaches., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

The three-dimensional (3D) structure of bacterial chromosomes is crucial for understanding chromosome function. With the growing availability of high-throughput chromosome conformation capture (3C/Hi-C) data, the 3D structure reconstruction algorithms have become powerful tools to study bacterial chromosome structure and function. It is highly desired to have a recommendation on the chromosome structure reconstruction tools to facilitate the prokaryotic 3D genomics. In this work, we review existing chromosome 3D structure reconstruction algorithms and classify them based on their underlying computational models into two categories: constraint-based modeling and thermodynamics-based modeling. We briefly compare these algorithms utilizing 3C/Hi-C datasets and fluorescence microscopy data obtained from Escherichia coli and Caulobacter crescentus, as well as simulated datasets. We discuss current challenges in the 3D reconstruction algorithms for bacterial chromosomes, primarily focusing on software usability. Finally, we briefly prospect future research directions for bacterial chromosome structure reconstruction algorithms., (© The Author(s) 2024. Published by Oxford University Press.)

Importance: Bacterial strains and clonal complexes are two cornerstone concepts for microbiology that remain loosely defined, which confuses communication and research. Here we identify a natural gap in genome sequence comparisons among isolate genomes of all well-sequenced species that has gone unnoticed so far and could be used to more accurately and precisely define these and related concepts compared to current methods. These findings advance the molecular toolbox for accurately delineating and following the important units of diversity within prokaryotic species and thus should greatly facilitate future epidemiological and micro-diversity studies across clinical and environmental settings., Competing Interests: The authors declare no conflict of interest.

Importance: The Flankophile pipeline enables the analysis and visualization of flanking regions of prokaryotic sequences of interest on large data sets in one step and in a consistent manner. A specific tool for flanking region analysis with automated visualization has not been developed before, and Flankophile will make flanking region analysis easier and accessible to more people. Flankophile will be especially useful in the field of genomic epidemiology of acquired antimicrobial resistance genes. Here, information from flanking region sequences can be instrumental in rejecting or supporting the possibility of a recent common source of the same resistance gene found in different samples., Competing Interests: The authors declare no conflict of interest.

Indonesia's deep-sea microbial communities remain poorly understood, prompting the need for comprehensive investigations. This study aimed to assess the bacterial and archaeal diversities in northwestern Arafura deep-sea sediments, spanning depths of 100 to 1,457 m using a 16S rRNA based-metagenomic sequencing approach, without technical and biological replicates. Principal component analyses based on the Bray-Curtis dissimilarity index indicated that most of the bacterial and archaeal communities were habitat-specific and influenced by depth. The most prevalent known bacterial phylotypes were detected from all samples belonging to the phylum of Desulfobacteriota, Pseudomonadota, and Firmicutes. In addition, the samples also harbored diverse members of the Archaea domain, including Crenarchaeota, Nanoarchaeota and Haloarchaeota. Notably, the sequencing data revealed the significant presence of rare prokaryotic taxa, including uncultured counterparts with less than 1% abundance. The findings suggest that novel and rare prokaryotic taxa are abundant in northwestern Arafura deep-sea ecosystem, offering unique opportunities for further bioprospecting and functional ecology studies., (© 2024. The Author(s).)

Duplication is a major route for the emergence of new gene functions. However, the emergence of new gene functions via this route may be reduced in prokaryotes, as redundant genes are often rapidly purged. In lineages with compact, streamlined genomes, it thus appears challenging for novel function to emerge via duplication and divergence. A further pressure contributing to gene loss occurs under Black Queen dynamics, as cheaters that lose the capacity to produce a public good can instead acquire it from neighbouring producers. We propose that Black Queen dynamics can favour the emergence of new function because, under an emerging Black Queen dynamic, there is high gene redundancy spread across a community of interacting cells. Using computational modelling, we demonstrate that new gene functions can emerge under Black Queen dynamics. This result holds even if there is deletion bias due to low duplication rates and selection against redundant gene copies resulting from the high cost associated with carrying a locus. However, when the public good production costs are high, Black Queen dynamics impede the fixation of new functions. Our results expand the mechanisms by which new gene functions can emerge in prokaryotic systems., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Society for Microbial Ecology.)

The formation of a stable complex between proteins lies at the core of a wide variety of biological processes and has been the focus of countless experiments. The huge amount of information contained in the protein structural interactome in the Protein Data Bank can now be used to characterise and classify the existing biological interfaces. We here introduce ARCTIC-3D, a fast and user-friendly data mining and clustering software to retrieve data and rationalise the interface information associated with the protein input data. We demonstrate its use by various examples ranging from showing the increased interaction complexity of eukaryotic proteins, 20% of which on average have more than 3 different interfaces compared to only 10% for prokaryotes, to associating different functions to different interfaces. In the context of modelling biomolecular assemblies, we introduce the concept of "recognition entropy", related to the number of possible interfaces of the components of a protein-protein complex, which we demonstrate to correlate with the modelling difficulty in classical docking approaches. The identified interface clusters can also be used to generate various combinations of interface-specific restraints for integrative modelling. The ARCTIC-3D software is freely available at github.com/haddocking/arctic3d and can be accessed as a web-service at wenmr.science.uu.nl/arctic3d., (© 2024. The Author(s).)

Microorganisms encode most of the functions of life on Earth. However, conventional research has primarily focused on specific environments such as humans, soil and oceans, leaving the distribution of functional families throughout the global biosphere poorly comprehended. Here, we present the database of the global distribution of prokaryotic protein families (GDPF, http://bioinfo.qd.sdu.edu.cn/GDPF/), a data resource on the distribution of functional families across the global biosphere. GDPF provides global distribution information for 36 334 protein families, 19 734 superfamilies and 12 089 KEGG (Kyoto Encyclopedia of Genes and Genomes) orthologs from multiple source databases, covering typical environments such as soil, oceans, animals, plants and sediments. Users can browse, search and download the distribution data of each entry in 10 000 global microbial communities, as well as conduct comparative analysis of distribution disparities among multiple entries across various environments. The GDPF data resource contributes to uncovering the geographical distribution patterns, key influencing factors and macroecological principles of microbial functions at a global level, thereby promoting research in Earth ecology and human health., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Pangenomes exhibit remarkable variability in many prokaryotic species, much of which is maintained through the processes of horizontal gene transfer and gene loss. Repeated acquisitions of near-identical homologs can easily be observed across pangenomes, leading to the question of whether these parallel events potentiate similar evolutionary trajectories, or whether the remarkably different genetic backgrounds of the recipients mean that postacquisition evolutionary trajectories end up being quite different. In this study, we present a machine learning method that predicts the presence or absence of genes in the Escherichia coli pangenome based on complex patterns of the presence or absence of other accessory genes within a genome. Our analysis leverages the repeated transfer of genes through the E. coli pangenome to observe patterns of repeated evolution following similar events. We find that the presence or absence of a substantial set of genes is highly predictable from other genes alone, indicating that selection potentiates and maintains gene-gene co-occurrence and avoidance relationships deterministically over long-term bacterial evolution and is robust to differences in host evolutionary history. We propose that at least part of the pangenome can be understood as a set of genes with relationships that govern their likely cohabitants, analogous to an ecosystem's set of interacting organisms. Our findings indicate that intragenomic gene fitness effects may be key drivers of prokaryotic evolution, influencing the repeated emergence of complex gene-gene relationships across the pangenome., Competing Interests: Competing interests statement:The authors declare no competing interest.

Prokaryotes are known to produce and secrete a broad range of biopolymers with a high functional and structural heterogeneity, often with critical duties in the bacterial physiology and ecology. Among these, exopolysaccharides (EPS) play relevant roles in the interaction of bacteria with eukaryotic hosts. EPS can help to colonize the host and assist in bacterial survival, making this interaction more robust by facilitating the formation of structured biofilms. In addition, they are often key molecules in the specific recognition mechanisms involved in both beneficial and pathogenic bacteria-host interactions. A novel EPS known as MLG (Mixed-Linkage β-Glucan) was recently discovered in rhizobia, where it participates in bacterial aggregation and biofilm formation and is required for efficient attachment to the roots of their legume host plants. MLG is the first and, so far, the only reported linear Mixed-Linkage β-glucan in bacteria, containing a perfect alternation of β (1 → 3) and β (1 → 4) bonds. A phylogenetic study of MLG biosynthetic genes suggests that far from being exclusive of rhizobia, different soil and plant-associated bacteria likely produce MLG, adding this novel polymer to the plethora of surface polysaccharides that help bacteria thrive in the changing environment and to establish successful interactions with their hosts.In this work, a quantification method for MLG is proposed. It relays on the hydrolysis of MLG by a specific enzyme (lichenase), and the subsequent quantification of the released disaccharide (laminaribiose) by the phenol-sulfuric acid method. The protocol has been set up and optimized for its use in 96-well plates, which makes it suitable for high-throughput screening (HTS) approaches. This method stands out by its fast processing, technical simplicity, and capability to handle multiple samples and biological replicates at a time., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

So far, bacterial regulatory sRNAs of length less than 50 nucleotides have been poorly understood, and a low number of such molecules has been identified. The first microRNA-size functional ribonucleic acid occurring in a bacterial cell has been described only recently, and it was found to be encoded by a bacteriophage. One of the reasons for such a scarcity in this field is the lack of procedures intended for the isolation and selection of molecules of this size from bacterial cells. To meet these difficulties, we describe here the few-step procedure of isolation, purification, selection, and sequencing library preparation that is dedicated to the fraction of very small, bacterial RNA molecules., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Large-scale and cost-less production of double-stranded RNA (dsRNA) is the basis for the widespread application of dsRNA in agriculture. Bidirectional transcription of target sequence in RNase III-deficient Escherichia coli strain HT115 (DE3) is an efficient way to produce large amounts of dsRNA. Here, we present a detailed method for the production of dsRNA by bidirectional transcription in E. coli from vector construction, induction of expression by isopropylthio-β-galactoside (IPTG), and purification of dsRNA from E. coli., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Prokaryotic Argonautes (pAgos) are an emerging class of programmable endonucleases that are believed to be more flexible than existing CRISPR-Cas systems and have significant potential for biotechnology. Current applications of pAgos include a myriad of molecular diagnostics and in vitro DNA assembly tools. However, efforts have historically been centered on thermophilic pAgo variants. To enable in vivo biotechnological applications such as gene editing, focus has shifted to pAgos from mesophilic organisms. We discuss what is known of pAgos, how they are being developed for various applications, and strategies to overcome current challenges to in vivo applications in prokaryotes and eukaryotes., Competing Interests: Declaration of interests The authors declare no conflicts of interest., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Simultaneous understanding of both population and ecosystem dynamics is crucial in an era marked by the degradation of ecosystem services. Experimental ecosystems are a powerful tool for understanding these dynamics; however, they often face technical challenges, typically falling into two categories: "complex but with limited replicability microcosms" and "highly replicable but overly simplistic microcosms." Herein, we present a high-throughput synthetic microcosm system comprising 12 functionally and phylogenetically diverse microbial species. These species are axenically culturable, cryopreservable, and can be measured noninvasively via microscopy, aided by machine learning. This system includes prokaryotic and eukaryotic producers and decomposers, and eukaryotic consumers to ensure functional redundancy. Our model system exhibited key features of a complex ecosystem: (i) various positive and negative interspecific interactions, (ii) higher-order interactions beyond two-species dynamics, (iii) probabilistic dynamics leading to divergent outcomes, and (iv) stable nonlinear transitions. We identified several conditions under which at least one species from each of the three functional groups-producers, consumers, and decomposers-and one functionally redundant species, persisted for over six months. These conditions set the stage for detailed investigations in the future. Given its designability and experimental replicability, our model ecosystem offers a promising platform for deeper insights integrating both population and ecosystem dynamics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Bacterial secretion systems are among the largest protein complexes in prokaryotes and display remarkably complex architectures. Their assembly often follows clearly defined pathways. Deciphering these pathways not only reveals how bacteria accomplish to build these large functional complexes but can provide crucial information on the interactions and subcomplexes within secretion systems, their distribution within the bacterium, and even functional insights. Fluorescence microscopy provides a powerful tool for biological imaging, which presents an interesting method to accurately define the biogenesis of macromolecular complexes using fluorescently labeled components. Here, I describe the use of this method to decipher the assembly pathway of bacterial secretion systems., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Importance: Virus-induced host lysis contributes up to 40% of total prokaryotic mortality and plays crucial roles in shaping microbial composition and diversity in the ocean. Nonetheless, what taxon-specific cell lysis is caused by viruses remains to be studied. The present study, therefore, examined the taxon-specific cell lysis and estimated its contribution to the variations in the rare and abundant microbial taxa. The results demonstrate that taxon-specific mortality differed in surface and bottom of the coastal environment. In addition, active rare taxa are more susceptible to heightened lytic pressure and suggested the importance of viral lysis in regulating the microbial community composition. These results improve our understanding of bottom-up (abiotic environmental variables) and top-down (viral lysis) controls contributing to microbial community assembly in the ocean., Competing Interests: The authors declare no conflict of interest.

Importance: Disturbances are major drivers of community succession in many microbial systems; however, relatively little is known about marine biofilm community succession, especially under antifouling disturbance. Antifouling technologies exert strong local disturbances on marine biofilms, and resulting biomass losses can be accompanied by shifts in biofilm community composition and succession. We address this gap in knowledge by bridging microbial ecology with antifouling technology development. We show that disturbance by shear can strongly alter marine biofilm community succession, acting as a selective filter influenced by frequency of exposure. Examining marine biofilm succession patterns with and without shear revealed stable associations between key prokaryotic and eukaryotic taxa, highlighting the importance of cross-domain assessment in future marine biofilm research. Describing how compounded top-down and bottom-up disturbances shape the succession of marine biofilms is valuable for understanding the assembly and stability of these complex microbial communities and predicting species invasiveness., Competing Interests: The authors declare no conflict of interest.

The basidiomycete Serpula lacrymans is responsible for major timber devastation in houses. Basidiomycetes are known to harbour a diverse but poorly understood microbial community of bacteria, archaea, yeasts and filamentous fungi. In this study, we used amplicon-sequencing to analyse the abundance and composition of prokaryotic communities associated with fruiting bodies of S. lacrymans and compared them to communities of surrounding material to access the 'background' community structure. Our findings indicate that bacterial genera cluster depended on sample type and that the main driver for microbial diversity is specimen, followed by sample origin. The most abundant bacterial phylum identified in the fruiting bodies was Pseudomonadota, followed by Actinomycetota and Bacteroidota. The prokaryote community of the mycelium was dominated by Actinomycetota, Halobacterota and Pseudomonadota. Actinomycetota was the most abundant phylum in both environment samples (infested timber and underground scree), followed by Bacillota in wood and Pseudomonadota in underground samples. Nocardioides, Pseudomonas, Pseudonochardia, Streptomyces and Rubrobacter spp. were among others found to comprise the core microbiome of S. lacrymans basidiocarps. This research contributes to the understanding of the holobiont S. lacrymans and gives hints to potential bacterial phyla important for its development and lifestyle., (© 2023 The Authors. Environmental Microbiology Reports published by Applied Microbiology International and John Wiley & Sons Ltd.)

Prokaryotic viruses, also known as bacteriophages, play crucial roles in regulating microbial communities and have the potential for phage therapy applications. Accurate prediction of phage-host interactions is essential for understanding the dynamics of these viruses and their impacts on bacterial populations. Numerous computational methods have been developed to tackle this challenging task. However, most existing prediction models can be constrained due to the substantial number of unknown interactions in comparison to the constrained diversity of available training data. To solve the problem, we introduce a model for prokaryotic virus host prediction with graph contrastive augmentation (PHPGCA). Specifically, we construct a comprehensive heterogeneous graph by integrating virus-virus protein similarity and virus-host DNA sequence similarity information. As the backbone encoder for learning node representations in the virus-prokaryote graph, we employ LGCN, a state-of-the-art graph embedding technique. Additionally, we apply graph contrastive learning to augment the node representations without the need for additional labels. We further conducted two case studies aimed at predicting the host range of multi-species phages, helping to understand the phage ecology and evolution., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Du et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Salinity is an important environmental factor in microbial ecology for affecting the microbial communities in diverse environments. Understanding the salinity adaptation mechanisms of a microbial community is a significant issue, while most previous studies only covered a narrow salinity range. Here, variations in seawater prokaryotic communities during the whole salt drying progression (salinity from 3% to 25%) were investigated. According to high-throughput sequencing results, the diversity, composition, and function of seawater prokaryotic communities varied significantly along the salinity gradient, expressing as decreased diversity, enrichment of some halophilic archaea, and powerful nitrate reduction in samples with high salt concentrations. More importantly, a sudden and dramatic alteration of prokaryotic communities was observed when salinity reached 16%, which was recognized as the change point. Combined with the results of network analysis, we found the increasing of complexity but decreasing of stability in prokaryotic communities when salinity exceeded the change point. Moreover, prokaryotic communities became more deterministic when salinity exceeded the change point due to the niche adaptation of halophilic species. Our study showed that substantial variations in seawater prokaryotic communities along an extremely wide salinity gradient, and also explored the underlying mechanisms regulating these changes., (© 2023 The Authors. Environmental Microbiology Reports published by Applied Microbiology International and John Wiley & Sons Ltd.)

The guanine/cytosine (GC) content of prokaryotic genomes is species-specific, taking values from 16% to 77%. This diversity of selection for GC content remains contentious. We analyse the correlations between GC content and a range of phenotypic and genotypic data in thousands of prokaryotes. GC content integrates well with these traits into r/K selection theory when phenotypic plasticity is considered. High GC-content prokaryotes are r-strategists with cheaper descendants thanks to a lower average amino acid metabolic cost, colonize unstable environments thanks to flagella and a bacillus form and are generalists in terms of resource opportunism and their defence mechanisms. Low GC content prokaryotes are K-strategists specialized for stable environments that maintain homeostasis via a high-cost outer cell membrane and endospore formation as a response to nutrient deprivation, and attain a higher nutrient-to-biomass yield. The lower proteome cost of high GC content prokaryotes is driven by the association between GC-rich codons and cheaper amino acids in the genetic code, while the correlation between GC content and genome size may be partly due to functional diversity driven by r/K selection. In all, molecular diversity in the GC content of prokaryotes may be a consequence of ecological r/K selection., (© 2023 Applied Microbiology International and John Wiley & Sons Ltd.)

In the Baltic Sea redoxcline, lysogenic viruses infecting prokaryotes have rarely been detected using the commonly used inducing agent mitomycin C. However, it is well known that not all viruses are induceable by mitomycin C and growing evidence suggests that changes in trophic conditions may trigger the induction of lysogenic viruses. We hypothesized that using antibiotics to simulate a strong change in trophic conditions for antibiotica-resistant cells due to reduced competition for resources might lead to the induction of lysogenic viruses into the lytic cycle within these cells. This hypothesis was tested by incubating prokaryotes obtained throughout the Baltic Sea redoxcline in seawater with substantially reduced numbers of viruses. We used a mixture of the protein synthesis-inhibiting antibiotics streptomycin and erythromycin to induce the desired changes in trophic conditions for resistant cells and at the same time ensuring that no progeny viruses were formed in sensitive cells. No inducible lysogenic viruses could be detected in incubations amended with mitomycin C. Yet, the presence of streptomycin and erythromycin increased virus-induced mortality of prokaryotes by 56–930% compared to controls, resulting in the induction of lysogenic viruses equivalent to 2–14% of in situ prokaryotic abundance. The results indicate the existence of a previously unrecognized induction mechanism for lysogenic viruses in the Baltic Sea redoxcline, as the mode of action distinctly differs between the used antibiotics (no virus production within affected cells) and mitomycin C (lysogenic viruses are produced within affected cells). Obtaining accurate experimental data on levels of lysogeny in prokaryotic host cells remains challenging, as relying on mitomycin C alone may severely underestimate lysogeny. [ABSTRACT FROM AUTHOR]

Intrinsic disorder is more abundant in eukaryotic than prokaryotic proteins. Methods predicting intrinsic disorder are based on the amino acid sequence of a protein. Therefore, there must exist an underlying difference in the sequences between eukaryotic and prokaryotic proteins causing the (predicted) difference in intrinsic disorder. By comparing proteins, from complete eukaryotic and prokaryotic proteomes, we show that the difference in intrinsic disorder emerges from the linker regions connecting Pfam domains. Eukaryotic proteins have more extended linker regions, and in addition, the eukaryotic linkers are significantly more disordered, 38% vs. 12-16% disordered residues. Next, we examined the underlying reason for the increase in disorder in eukaryotic linkers, and we found that the changes in abundance of only three amino acids cause the increase. Eukaryotic proteins contain 8.6% serine; while prokaryotic proteins have 6.5%, eukaryotic proteins also contain 5.4% proline and 5.3% isoleucine compared with 4.0% proline and ≈ 7.5% isoleucine in the prokaryotes. All these three differences contribute to the increased disorder in eukaryotic proteins. It is tempting to speculate that the increase in serine frequencies in eukaryotes is related to regulation by kinases, but direct evidence for this is lacking. The differences are observed in all phyla, protein families, structural regions and type of protein but are most pronounced in disordered and linker regions. The observation that differences in the abundance of three amino acids cause the difference in disorder between eukaryotic and prokaryotic proteins raises the question: Are amino acid frequencies different in eukaryotic linkers because the linkers are more disordered or do the differences cause the increased disorder? [ABSTRACT FROM AUTHOR]

Nanoparticles fabricated using medicinal plant extract have great potential in the area of nanomedicine. High surface‐to‐volume ratio of nanoparticle enhances the local active biomolecules concentration, leading to many fold increase in the medicinal potentials. The silver nanoparticles (AgNPs) fabricated using indigenous medicinal plants of India, Azadirachta indica and Syzygium cumini, have shown a significant effect on the viability of prokaryotic and eukaryotic cells. Biofabrication of AgNP was confirmed using different spectroscopic and microscopic techniques. Extraction and purification of AgNP from non‐conjugated plant moieties are done using centrifugation and size exclusion chromatography. The cytotoxic propensity of AgNP formulations was screened against Gram‐positive (Bacillus subtilis), Gram‐negative (Escherichia coli) bacteria, cancerous (HT1080) and non‐cancerous (HEK293) cell lines. The nanoparticle formulations showed a relatively higher cytotoxic propensity against Gram‐positive bacteria and cancerous cell lines. In addition, the surface roughness and reactive oxygen species (ROS) measurements indicated that AgNP formulations mediate the cell activity predominantly by ROS‐mediated disruptive change in membrane morphology upon direct interaction with the membrane. Hence, the nanoparticle formulations show an enhanced selective cytotoxic propensity towards Gram‐positive bacteria and cancerous cell lines. [ABSTRACT FROM AUTHOR]

The study of interfaces between engineered surfaces and prokaryotic cells is a subject whose actual relevance has been reinforced by the current outbreaks due to unknown viruses and antibiotic-resistant bacteria. Studies aiming at the development of antibacterial surfaces are based on two pillars: surface chemistry or topographical cues. This work reports the study of only the topographic aspect by the development of thin films of polyamide, which present attractive surface chemistry for bacterial adhesion. The same chemistry with only nano- or hierarchical nano- and micro-topography that mimics the extracellular matrix is obtained by sputter-depositing the thin films onto Si and polydimethylsiloxane (PDMS), respectively. The surface average roughness of the Si-modified surfaces was around 1 nm, while the hierarchical topography presented values from 750 to 1000 nm, with wavelengths and amplitudes ranging from 15–30 µm and 1–3 µm, respectively, depending on the deposition parameters. The surface topography, wettability, surface charge, and mechanical properties were determined and related to interface performance with two Gram+ and two Gram- bacterial strains. The overall results show that surfaces with only nano-topographic features present less density of bacteria, regardless of their cell wall composition or cell shape, if the appropriate surface chemistry is present.

Sequence comparison tools for metagenome-assembled genomes (MAGs) struggle with high-volume or low-quality data. We present skani ( https://github.com/bluenote-1577/skani ), a method for determining average nucleotide identity (ANI) via sparse approximate alignments. skani outperforms FastANI in accuracy and speed (>20× faster) for fragmented, incomplete MAGs. skani can query genomes against >65,000 prokaryotic genomes in seconds and 6 GB memory. skani unlocks higher-resolution insights for extensive, noisy metagenomic datasets., (© 2023. The Author(s).)

Ratios between viruses, heterotrophic prokaryotes and chlorophyll a are key indicators of microbial food structure and both virus-prokaryote and prokaryote-chlorophyll ratios have been proposed to decrease with system productivity. However, the mechanisms underlying these responses are still insufficiently resolved and their consistency across aquatic ecosystem types requires critical evaluation. We assessed microbial community ratios in highly productive African soda-lakes and used our data from naturally hypereutrophic systems which are largely underrepresented in literature, to complement earlier across-system meta-analyses. In contrast to marine and freshwater systems, prokaryote-chlorophyll ratios in African soda-lakes did not decrease along productivity gradients. High-resolution time series from two soda-lakes indicated that this lack of response could be driven by a weakened top-down control of heterotrophic prokaryotes. Our analysis of virus-prokaryote relationships, revealed a reduction of virus-prokaryote ratios by high suspended particle concentrations in soda-lakes. This effect, likely driven by the adsorption of free-living viruses, was also found in three out of four additionally analysed marine datasets. However, the decrease of virus-prokaryote ratios previously reported in highly productive marine systems, was neither detectable in soda-lakes nor freshwaters. Hence, our study demonstrates that system-specific analyses can reveal the diversity of mechanisms that structure microbial food-webs and shape their response to productivity increases.

Background: Genome-scale phylogenetic analysis based on core gene sets is routinely used in microbiological research. However, the techniques are still not approachable for individuals with little bioinformatics experience. Here, we present EasyCGTree, a user-friendly and cross-platform pipeline to reconstruct genome-scale maximum-likehood (ML) phylogenetic tree using supermatrix (SM) and supertree (ST) approaches., Results: EasyCGTree was implemented in Perl programming languages and was built using a collection of published reputable programs. All the programs were precompiled as standalone executable files and contained in the EasyCGTree package. It can run after installing Perl language environment. Several profile hidden Markov models (HMMs) of core gene sets were prepared in advance to construct a profile HMM database (PHD) that was enclosed in the package and available for homolog searching. Customized gene sets can also be used to build profile HMM and added to the PHD via EasyCGTree. Taking 43 genomes of the genus Paracoccus as the testing data set, consensus (a variant of the typical SM), SM, and ST trees were inferred via EasyCGTree successfully, and the SM trees were compared with those inferred via the pipelines UBCG and bcgTree, using the metrics of cophenetic correlation coefficients (CCC) and Robinson-Foulds distance (topological distance). The results suggested that EasyCGTree can infer SM trees with nearly identical topology (distance < 0.1) and accuracy (CCC > 0.99) to those of trees inferred with the two pipelines., Conclusions: EasyCGTree is an all-in-one automatic pipeline from input data to phylogenomic tree with guaranteed accuracy, and is much easier to install and use than the reference pipelines. In addition, ST is implemented in EasyCGTree conveniently and can be used to explore prokaryotic evolutionary signals from a different perspective. The EasyCGTree version 4 is freely available for Linux and Windows users at Github ( https://github.com/zdf1987/EasyCGTree4 )., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Stability of proteins at high temperature has been a topic of interest for many years, as this attribute is favourable for applications ranging from therapeutics to industrial chemical manufacturing. Our current understanding and methods for designing high-temperature stability into target proteins are inadequate. To drive innovation in this space, we have curated a large dataset, learn2thermDB, of protein-temperature examples, totalling 24 million instances, and paired proteins across temperatures based on homology, yielding 69 million protein pairs - orders of magnitude larger than the current largest. This important step of pairing allows for study of high-temperature stability in a sequence-dependent manner in the big data era. The data pipeline is parameterized and open, allowing it to be tuned by downstream users. We further show that the data contains signal for deep learning. This data offers a new doorway towards thermal stability design models., (© 2023. Springer Nature Limited.)