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Light is a key environmental component influencing many biological processes, particularly in prokaryotes such as archaea and bacteria. Light control techniques have revolutionized precise manipulation at molecular and cellular levels in recent years. Bacteria, with adaptability and genetic tractability, are promising candidates for light control studies. This review investigates the mechanisms underlying light activation in bacteria and discusses recent advancements focusing on light control methods and techniques for controlling bacteria. We delve into the mechanisms by which bacteria sense and transduce light signals, including engineered photoreceptors and light-sensitive actuators, and various strategies employed to modulate gene expression, protein function, and bacterial motility. Furthermore, we highlight recent developments in light-integrated methods of controlling microbial responses, such as upconversion nanoparticles and optical tweezers, which can enhance the spatial and temporal control of bacteria and open new horizons for biomedical applications.

Summary: Sequence technology advancements have led to an exponential increase in bacterial genomes, necessitating robust taxonomic classification methods. The Percentage Of Conserved Proteins (POCP), proposed initially by Qin et al. (2014), is a valuable metric for assessing prokaryote genus boundaries. Here, I introduce a computational pipeline for automated POCP calculation, aiming to enhance reproducibility and ease of use in taxonomic studies., Availability and Implementation: The POCP-nf pipeline uses DIAMOND for faster protein alignments, achieving similar sensitivity to BLASTP. The pipeline is implemented in Nextflow with Conda and Docker support and is freely available on GitHub under https://github.com/hoelzer/pocp. The open-source code can be easily adapted for various prokaryotic genome and protein datasets. Detailed documentation and usage instructions are provided in the repository., (© The Author(s) 2024. Published by Oxford University Press.)

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.)

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.)

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.)

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.)

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.)

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.)

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).)

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.)

Membrane coat proteins are essential players in the eukaryotic endomembrane traffic system. Previous work identified proteins with the membrane-coat architecture in prokaryotes, specifically in the Planctomycetes, Verrucomicrobia and Chlamydiae (PVC) superphylum, bacteria that display the most developed prokaryotic endomembrane system. Hence, the membrane coat-like (MCL) proteins are predicted to play a central role in this system but their actual function is still unknown. In this work we strengthened previous structure predictions for these prokaryotic MCL proteins. We also detected new putative MCL proteins in the Planctomycete Gemmata obscuriglobus. Structural analysis of these revealed the presence of additional domains apart from the β-propeller and α-solenoid combination, characteristic of the membrane-coat architecture. Functions associated with these domains include some related to carbohydrate or membrane/lipid binding. Using homology-based methods, we found MCL proteins in other bacterial phyla, but the most abundant hits are still restricted to Planctomycetes and Verrucomicrobia. Detailed inspection of neighbouring genes of MCL in G. obscuriglobus supports the idea that the function of these proteins is related to membrane manipulation. No significant hits were found in Archaea, including Asgard archaea. More than 10 years after their original detection, PVC bacteria are still uniquely linked to eukaryotes through the structure of the MCL proteins sustaining their endomembrane system., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: M. Leticia Ferrelli, Matias L. Pidre, and Damien P. Devos report financial support was provided by MSC program REFRACT MSCA RISE PROJECT 2019 (H2020 EU GA N 823886)., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Both eukaryotes and prokaryotes (archaea and bacteria) encode an arsenal of immune systems that protect the host against mobile genetic elements (MGEs) including viruses, plasmids, and transposons. Whereas Argonaute proteins (Agos) are best known for post-transcriptional gene silencing in eukaryotes, in all domains of life, members from the highly diverse Argonaute protein family act as programmable immune systems. To this end, Agos are programmed with small single-stranded RNA or DNA guides to detect and silence complementary MGEs. Across and within the different domains of life, Agos function in distinct pathways and MGE detection can trigger various mechanisms that provide immunity. In this review, we delineate the diverse immune pathways and underlying mechanisms for both eukaryotic Argonautes (eAgos) and prokaryotic Argonautes (pAgos)., Competing Interests: Declaration of Competing Interest D.C.S. has submitted several patent applications regarding the utilization of pAgos for nucleic acid detection and modification., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Prokaryotic adaptation is strongly influenced by the horizontal acquisition of beneficial traits via mobile genetic elements (MGEs), such as viruses/bacteriophages and plasmids. However, MGEs can also impose a fitness cost due to their often parasitic nature and differing evolutionary trajectories. In response, prokaryotes have evolved diverse immune mechanisms against MGEs. Recently, our understanding of the abundance and diversity of prokaryotic immune systems has greatly expanded. These defense systems can degrade the invading genetic material, inhibit genome replication, or trigger abortive infection, leading to population protection. In this review, we highlight these strategies, focusing on the most recent discoveries. The study of prokaryotic defenses not only sheds light on microbial evolution but also uncovers novel enzymatic activities with promising biotechnological applications., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Short prokaryotic argonaute (pAgo) and toll/interleukin-1 receptor/resistance protein (TIR)-analog of PAZ (APAZ) form a heterodimeric SPARTA complex that provides immunity to its prokaryotic host through an abortive infection mechanism. Monomeric SPARTA senses foreign RNA/DNA duplexes to assemble an active tetramer resulting in cell death by nicotinamide adenine dinucleotide (oxidized form) (NAD) depletion via an unknown mechanism. We report nine structures of SPARTA in different functional states at a resolution range of 4.2 to 2.9 angstroms, revealing its activation mechanism. Inactive SPARTA monomers bind to RNA/DNA duplexes to form symmetric dimers mediated by the association of Ago subunits. The initiation of tetramer assembly induces flexibility of the TIR domains enabling a symmetry-breaking rotational movement of a TIR domain in the dimer units which facilitates the TIR oligomerization, resulting in the formation of the substrate binding pocket and the activation of the SPARTA complex's NADase activity. Our findings provide detailed structural and mechanistic insights into activating a short argonaute defense system.

Prokaryotic Argonaute (pAgo) proteins are programmable nucleases with great promise in genetic engineering and biotechnology. Previous studies identified several DNA-targeting pAgo nucleases from mesophilic and thermophilic prokaryotic species that are active in various temperature ranges. However, the effects of temperature on the specificity of target recognition and cleavage by pAgos have not been studied. Here, we describe a thermostable pAgo nuclease from the thermophilic bacterium Thermobrachium celere, TceAgo. We show that TceAgo preferentially uses 5'-phosphorylated small DNA guides and can perform specific cleavage of both single-stranded and double-stranded DNA substrates in a wide range of temperatures. Single-nucleotide mismatches between guide and target molecules differently change the reaction efficiency depending on the mismatch position, with the fidelity of target recognition greatly increased at elevated temperatures. Thus, TceAgo can serve as a tool to allow specific detection and cleavage of DNA targets in a temperature-dependent manner. The results demonstrate that the specificity of programmable nucleases can be strongly affected by the reaction conditions, which should be taken into account when using these nucleases in various in vitro and in vivo applications., 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 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.)

Among the Arctic seas, the largest volume of river runoff (~45% of the total river-water inflow into the Arctic Ocean) enters the Siberian Kara Sea. The viral communities of the Kara Sea are important for the functioning of the marine ecosystem. Studies of virus-prokaryote interactions on the Kara Sea shelf have been conducted only in spring and autumn. Here, we investigated the abundance of free viruses, viruses attached to prokaryotes, and pico-sized detrital particles; the morphology (shape and size) of the viruses, viral infection and virus-mediated mortality of prokaryotes in early summer, i.e ., during a seasonal ice melting period and maximum inflow of river-water volumes with high concentrations of dissolved and suspended organic carbon. Seawater samples for microbial analyses were collected across the Kara Sea shelf zone on board the Norilskiy Nickel as a research platform from June 29 to July 15, 2018. Abundances of prokaryotes (range (0.6-25.3) × 10 5 cells mL -1 ) and free viruses (range (10-117) × 10 5 viruses mL -1 ) were correlated (r = 0.63, p = 0.005) with an average virus: prokaryote ratio of 23.9 ± 5.3. The abundance of free viruses and viral-mediated mortality of prokaryotes were significantly higher in early summer than in early spring and autumn. Free viruses with a capsid diameter of 16-304 nm were recorded in the examined water samples. Waters in the Kara Sea shelf contained high concentrations of suspended organic particles 0.25-4.0 µm in size (range (0.6-25.3) × 10 5 particles mL -1 ). The proportions of free viruses, viruses attached to prokaryotes, and viruses attached to pico-sized detrital particles were 89.8 ± 6.0%, 2.2 ± 0.6% and 8.0 ± 1.3%, respectively, of the total virioplankton abundance (on average (61.5 ± 6.2) × 10 5 viruses mL -1 ). Viruses smaller than 60 nm clearly dominated at all studied sites. The majority of free viruses were not tailed. We estimated that an average of 1.4% (range 0.4-3.5%) of the prokaryote community was visibly infected by viruses, suggesting that a significant proportion of prokaryotic secondary production, 11.4% on average (range 4.0-34.0%), was lost due to viral lysis. There was a negative correlation between the abundance of pico-sized detrital particles and the frequency of visibly infected prokaryotic cells: r = -0.67, p = 0.0008., Competing Interests: The authors declare there are no competing interests., (© 2023 Kopylov et al.)

The pangenome is the set of all genes present in a prokaryotic population. Most pangenomes contain many accessory genes of low and intermediate frequencies. Different population genetics processes contribute to the shape of these pangenomes, namely selection and fitness-independent processes such as gene transfer, gene loss, and migration. However, their relative importance is unknown and highly debated. Here, we argue that the debate around prokaryotic pangenomes arose due to the imprecise application of population genetics models. Most importantly, two different processes of horizontal gene transfer act on prokaryotic populations, which are frequently confused, despite their fundamentally different behavior. Genes acquired from distantly related organisms (termed here acquiring gene transfer) are most comparable to mutation in nucleotide sequences. In contrast, gene gain within the population (termed here spreading gene transfer) has an effect on gene frequencies that is identical to the effect of positive selection on single genes. We thus show that selection and fitness-independent population genetic processes affecting pangenomes are indistinguishable at the level of single gene dynamics. Nevertheless, population genetics processes are fundamentally different when considering the joint distribution of all accessory genes across individuals of a population. We propose that, to understand to which degree the different processes shaped pangenome diversity, the development of comprehensive models and simulation tools is mandatory. Furthermore, we need to identify summary statistics and measurable features that can distinguish between the processes, where considering the joint distribution of accessory genes across individuals of a population will be particularly relevant., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

Horizontal gene transfer (HGT) and the resulting patterns of gene gain and loss are a fundamental part of bacterial evolution. Investigating these patterns can help us to understand the role of selection in the evolution of bacterial pangenomes and how bacteria adapt to a new niche. Predicting the presence or absence of genes can be a highly error-prone process that can confound efforts to understand the dynamics of horizontal gene transfer. This review discusses both the challenges in accurately constructing a pangenome and the potential consequences errors can have on downstream analyses. We hope that by summarizing these issues researchers will be able to avoid potential pitfalls, leading to improved bacterial pangenome analyses.

The evolution of genomes in all life forms involves two distinct, dynamic types of genomic changes: gene duplication (and loss) that shape families of paralogous genes and extension (and contraction) of low-complexity regions (LCR), which occurs through dynamics of short repeats in protein-coding genes. Although the roles of each of these types of events in genome evolution have been studied, their co-evolutionary dynamics is not thoroughly understood. Here, by analyzing a wide range of genomes from diverse bacteria and archaea, we show that LCR and paralogy represent two distinct routes of evolution that are inversely correlated. The emergence of LCR is a prominent evolutionary mechanism in fast evolving, young protein families, whereas paralogy dominates the comparatively slow evolution of old protein families. The analysis of multiple prokaryotic genomes shows that the formation of LCR is likely a widespread, transient evolutionary mechanism that temporally and locally affects also ancestral functions, but apparently, fades away with time, under mutational and selective pressures, yielding to gene paralogy. We propose that compensatory relationships between short-term and longer-term evolutionary mechanisms are universal in the evolution of life.

CRISPR-Cas and prokaryotic Argonaute (pAgo) are nucleic acid (NA)-guided defense systems that protect prokaryotes against the invasion of mobile genetic elements. Previous studies established that they are directed by NA fragments (guides) to recognize invading complementary NA (targets), and that they cleave the targets to silence the invaders. Nevertheless, growing evidence indicates that many CRISPR-Cas and pAgo systems exploit the abortive infection (Abi) strategy to confer immunity. The CRISPR-Cas and pAgo Abi systems typically sense invaders using the NA recognition ability and activate various toxic effectors to kill the infected cells to prevent the invaders from spreading. This review summarizes the diverse mechanisms of these CRISPR-Cas and pAgo systems, and highlights their critical roles in the arms race between microbes and invaders., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The distribution of prokaryotic metabolism between maintenance and growth activities has a profound impact on the transformation of carbon substrates to either biomass or CO 2 . Knowledge of key factors influencing prokaryotic maintenance respiration is, however, highly limited. This mesocosm study validated the significance of prokaryotic maintenance respiration by mimicking temperature and nutrients within levels representative of winter and summer conditions. A global range of growth efficiencies (0.05-0.57) and specific growth rates (0.06-2.7 d -1 ) were obtained. The field pattern of cell-specific respiration versus specific growth rate and the global relationship between growth efficiency and growth rate were reproduced. Maintenance respiration accounted for 75% and 15% of prokaryotic respiration corresponding to winter and summer conditions, respectively. Temperature and nutrients showed independent positive effects for all prokaryotic variables except abundance and cell-specific respiration. All treatments resulted in different taxonomic diversity, with specific populations of amplicon sequence variants associated with either maintenance or growth conditions. These results validate a significant relationship between specific growth and respiration rate under productive conditions and show that elevated prokaryotic maintenance respiration can occur under cold and oligotrophic conditions. The experimental design provides a tool for further study of prokaryotic energy metabolism under realistic conditions at the mesocosm scale., (© 2022 The Authors. Environmental Microbiology published by Applied Microbiology International and John Wiley & Sons Ltd.)

The necessity to record and store biological data is increasing in due course of time. However, it is quite difficult to understand biological mechanisms and keep a track of these events in some storage mediums. DNA (deoxyribonucleic acid) is the best candidate for the storage of cellular events in the biological system. It is energy efficient as well as stable at the same time. DNA-based writers and memory devices are continually evolving and finding new avenues in terms of their wide range of applications. Among all the DNA-based storage devices that employ enzymes like recombinases, nucleases, integrases, and polymerases, one of the most popular tools used for these devices is the emerging and versatile CRISPR Cas technology. CRISPR Cas is a prokaryotic immune system that keeps a memory of viral attacks and protects prokaryotes from potential future infections. The main aim of this short review is to study such molecular recorders and writers that employ CRISPR Cas technologies and obtain an in-depth overview of the mechanisms involved and the applications of these molecular devices., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Identification of microbial functional association networks allows interpretation of biological phenomena and a greater understanding of the molecular basis of pathogenicity and also underpins the formulation of control measures. Here, we describe PPNet, a tool that uses genome information and analysis of phylogenetic profiles with binary similarity and distance measures to derive large-scale bacterial gene association networks of a single species. As an exemplar, we have derived a functional association network in the pig pathogen Streptococcus suis using 81 binary similarity and dissimilarity measures which demonstrates excellent performance based on the area under the receiver operating characteristic (AUROC), the area under the precision-recall (AUPR), and a derived overall scoring method. Selected network associations were validated experimentally by using bacterial two-hybrid experiments. We conclude that PPNet, a publicly available (https://github.com/liyangjie/PPNet), can be used to construct microbial association networks from easily acquired genome-scale data. IMPORTANCE This study developed PPNet, the first tool that can be used to infer large-scale bacterial functional association networks of a single species. PPNet includes a method for assigning the uniqueness of a bacterial strain using the average nucleotide identity and the average nucleotide coverage. PPNet collected 81 binary similarity and distance measures for phylogenetic profiling and then evaluated and divided them into four groups. PPNet can effectively capture gene networks that are functionally related to phenotype from publicly prokaryotic genomes, as well as provide valuable results for downstream analysis and experiment testing.

Restrictions placed on the distribution of biological material by the legislation of countries such as India, South Africa, or Brazil exclude strains that could serve as type material for the validation or valid publication of prokaryotic species names. This problem goes beyond prokaryotic taxonomy and is also relevant for other areas of biological research., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Ice-binding proteins (IBPs) are a group of ecologically and biotechnologically relevant enzymes produced by psychrophilic organisms. Although putative IBPs containing the domain of unknown function (DUF) 3494 have been identified in many taxa of polar microbes, our knowledge of their genetic and structural diversity in natural microbial communities is limited. Here, we used samples from sea ice and sea water collected in the central Arctic Ocean as part of the MOSAiC expedition for metagenome sequencing and the subsequent analyses of metagenome-assembled genomes (MAGs). By linking structurally diverse IBPs to particular environments and potential functions, we reveal that IBP sequences are enriched in interior ice, have diverse genomic contexts and cluster taxonomically. Their diverse protein structures may be a consequence of domain shuffling, leading to variable combinations of protein domains in IBPs and probably reflecting the functional versatility required to thrive in the extreme and variable environment of the central Arctic Ocean.

The Genome Taxonomy Database (GTDB) is a taxonomic framework that defines prokaryotic taxa as monophyletic groups in concatenated protein reference trees according to systematic criteria. This has resulted in a substantial number of changes to existing classifications (https://gtdb.ecogenomic.org). In the case of union of taxa, GTDB names were applied based on the priority of publication. The division of taxa or change in rank led to the formation of new Latin names above the rank of genus that were only made publicly available via the GTDB website without associated published taxonomic descriptions. This has sometimes led to confusion in the literature and databases. A number of the provisional GTDB names were later published in other studies, while many still lack authorships. To reduce further confusion, here we propose names and descriptions for 329 GTDB-defined prokaryotic taxa, 223 of which are suitable for validation under the International Code of Nomenclature of Prokaryotes (ICNP) and 49 under the Code of Nomenclature of Prokaryotes described from Sequence Data (SeqCode). For the latter, we designated 23 genomes as type material. An additional 57 taxa that do not currently satisfy the validation criteria of either code are proposed as Candidatus., (© The Author(s) 2023. Published by Oxford University Press on behalf of FEMS.)

The interpretation of genomic, transcriptomic and other microbial 'omics data is highly dependent on the availability of well-annotated genomes. As the number of publicly available microbial genomes continues to increase exponentially, the need for quality control and consistent annotation is becoming critical. We present proGenomes3, a database of 907 388 high-quality genomes containing 4 billion genes that passed stringent criteria and have been consistently annotated using multiple functional and taxonomic databases including mobile genetic elements and biosynthetic gene clusters. proGenomes3 encompasses 41 171 species-level clusters, defined based on universal single copy marker genes, for which pan-genomes and contextual habitat annotations are provided. The database is available at http://progenomes.embl.de/., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Compared with conventional comparative genomics, the recent studies in pan-genomics have provided further insights into species genomic dynamics, taxonomy and identification, pathogenicity and environmental adaptation. To better understand genome characteristics of species of interest and to fully excavate key metabolic and resistant genes and their conservations and variations, here we present ProPan (https://ngdc.cncb.ac.cn/propan), a public database covering 23 archaeal species and 1,481 bacterial species (in a total of 51,882 strains) for comprehensively profiling prokaryotic pan-genome dynamics. By analyzing and integrating these massive datasets, ProPan offers three major aspects for the pan-genome dynamics of the species of interest: 1) the evaluations of various species' characteristics and composition in pan-genome dynamics; 2) the visualization of map association, the functional annotation and presence/absence variation for all contained species' gene clusters; 3) the typical characteristics of the environmental adaptation, including resistance genes prediction of 126 substances (biocide, antimicrobial drug and metal) and evaluation of 31 metabolic cycle processes. Besides, ProPan develops a very user-friendly interface, flexible retrieval and multi-level real-time statistical visualization. Taken together, ProPan will serve as a weighty resource for the studies of prokaryotic pan-genome dynamics, taxonomy and identification as well as environmental adaptation., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Horizontal gene transfer (HGT) plays a critical role in the evolution and diversification of many microbial species. The resulting dynamics of gene gain and loss can have important implications for the development of antibiotic resistance and the design of vaccine and drug interventions. Methods for the analysis of gene presence/absence patterns typically do not account for errors introduced in the automated annotation and clustering of gene sequences. In particular, methods adapted from ecological studies, including the pangenome gene accumulation curve, can be misleading as they may reflect the underlying diversity in the temporal sampling of genomes rather than a difference in the dynamics of HGT. Here, we introduce Panstripe, a method based on generalized linear regression that is robust to population structure, sampling bias, and errors in the predicted presence/absence of genes. We show using simulations that Panstripe can effectively identify differences in the rate and number of genes involved in HGT events, and illustrate its capability by analyzing several diverse bacterial genome data sets representing major human pathogens., (© 2023 Tonkin-Hill et al.; Published by Cold Spring Harbor Laboratory Press.)

To date, the vast majority of prokaryotic organisms escapes detailed characterization because they cannot be isolated in axenic cultures. These organisms are referred to as microbial dark matter. Targeted labelling and sorting of these microorganisms pave the way for single-cell, enrichment, or cultivation approaches. In this review, we describe an array of different methods ranging from labeling-free to specific labelling techniques. In addition, different cell sorting methods and their combinations with targeting strategies are summarized and downstream applications like sequencing and cultivation are reviewed. Recent advances, challenges, and limitations of the particular methods are discussed with respect to cell viability, genome integrity as well as throughput, in order to help researchers select the most suitable methods for their specific research questions., (© 2023 The Author(s). Published by S. Karger AG, Basel.)

Infrared spectroscopy is used for the chemical characterization of prokaryotes. However, its application has been limited to cell aggregates and lipid extracts because of the relatively low spatial resolution of diffraction. We herein report optical photothermal infrared (O-PTIR) spectroscopy of prokaryotes for a domain-level diagnosis at the single-cell level. The technique provided infrared spectra of individual bacterial as well as archaeal cells, and the resulting aliphatic CH 3 /CH 2 intensity ratios showed domain-specific signatures, which may reflect distinctive cellular lipid compositions; however, there was interference by other cellular components. These results suggest the potential of O-PTIR for a domain-level diagnosis of single prokaryotic cells in natural environments.

By denaturing proteins and promoting the formation of multiprotein complexes, protein phosphorylation has important effects on the activity of protein functional molecules and cell signaling. The regulation of protein phosphorylation allows microbes to respond rapidly and reversibly to specific environmental stimuli or niches, which is closely related to the molecular mechanisms of bacterial drug resistance. Accurate prediction of phosphorylation sites (p-site) of prokaryotes can contribute to addressing bacterial resistance and providing new perspectives for developing novel antibacterial drugs. Most existing studies focus on human phosphorylation sites, while tools targeting phosphorylation site identification of prokaryotic proteins are still relatively scarce. This study designs a capsule network-based prediction technique for p-site in prokaryotes. To address the poor scalability and unreliability of dynamic routing processes in the output space of capsule networks, a more reliable way is introduced to learn the consistency between capsules. We incorporate a self-attention mechanism into the routing algorithm to capture the global information of the capsule, reducing the computational effort while enriching the representation capability of the capsule. Aiming at the weak robustness of the model, EcapsP improves the prediction accuracy and stability by introducing shortcuts and unconditional reconfiguration. In addition, the study compares and analyzes the prediction performance based on word vectors, physicochemical properties, and mixing characteristics in predicting serine (Ser/S), threonine (Thr/T), and tyrosine (Tyr/Y) p-site. The comprehensive experimental results show that the accuracy of the developed technique is close to 70% for the identification of the three phosphorylation sites in prokaryotes. Importantly, in side-by-side comparisons with other state-of-the-art predictors, our method improves the Matthews correlation coefficient (MCC) by approximately 7%. The results demonstrate the superiority of EcapsP in terms of high performance and reliability.

Horizontal gene transfer (HGT) is a major source of phenotypic innovation and a mechanism of niche adaptation in prokaryotes. Quantification of HGT is critical to decipher its myriad roles in microbial evolution and adaptation. Advances in genome sequencing and bioinformatics have augmented our ability to understand the microbial world, particularly the direct or indirect influence of HGT on diverse life forms. Methods for detecting HGT can be classified into phylogenetic-based and parametric or composition-based approaches. Here, we exploited the complementary strengths of both the approaches to construct a high confidence horizontal gene flow network. Our network is unique in its ability to detect the transfer of native genes of a genome to genomes from other taxa, thus establishing donor and recipient organisms (taxa), rather than through a post hoc analysis as is the practice with several other approaches. The scale-free horizontal gene flow network presented here provides new insights into modes of transfer for the exchange of genetic information and also illuminates differential gene flow across phyla.

Programmable nucleases are the most important tool for manipulating the genes and genomes of both prokaryotes and eukaryotes. Since the end of the 20th century, many approaches were developed for specific modification of the genome. The review briefly considers the advantages and disadvantages of the main genetic editors known to date. The main attention is paid to programmable nucleases from the family of prokaryotic Argonaute proteins. Argonaute proteins can recognize and cleave DNA sequences using small complementary guide molecules and play an important role in protecting prokaryotic cells from invading DNA. Argonaute proteins have already found applications in biotechnology for targeted cleavage and detection of nucleic acids and can potentially be used for genome editing.

Most prokaryotes are not available as pure cultures and therefore ineligible for naming under the rules and recommendations of the International Code of Nomenclature of Prokaryotes (ICNP). Here we summarize the development of the SeqCode, a code of nomenclature under which genome sequences serve as nomenclatural types. This code enables valid publication of names of prokaryotes based upon isolate genome, metagenome-assembled genome or single-amplified genome sequences. Otherwise, it is similar to the ICNP with regard to the formation of names and rules of priority. It operates through the SeqCode Registry ( https://seqco.de/ ), a registration portal through which names and nomenclatural types are registered, validated and linked to metadata. We describe the two paths currently available within SeqCode to register and validate names, including Candidatus names, and provide examples for both. Recommendations on minimal standards for DNA sequences are provided. Thus, the SeqCode provides a reproducible and objective framework for the nomenclature of all prokaryotes regardless of cultivability and facilitates communication across microbiological disciplines., (© 2022. The Author(s).)

Background: Evolutionary rate is a key characteristic of gene families that is linked to the functional importance of the respective genes as well as specific biological functions of the proteins they encode. Accurate estimation of evolutionary rates is a challenging task that requires precise phylogenetic analysis. Here we present an easy to estimate protein family level measure of sequence variability based on alignment column homogeneity in multiple alignments of protein sequences from Clade-Specific Clusters of Orthologous Genes (csCOGs)., Results: We report genome-wide estimates of variability for 8 diverse groups of bacteria and archaea and investigate the connection between variability and various genomic and biological features. The variability estimates are based on homogeneity distributions across amino acid sequence alignments and can be obtained for multiple groups of genomes at minimal computational expense. About half of the variance in variability values can be explained by the analyzed features, with the greatest contribution coming from the extent of gene paralogy in the given csCOG. The correlation between variability and paralogy appears to originate, primarily, not from gene duplication, but from acquisition of distant paralogs and xenologs, introducing sequence variants that are more divergent than those that could have evolved in situ during the lifetime of the given group of organisms. Both high-variability and low-variability csCOGs were identified in all functional categories, but as expected, proteins encoded by integrated mobile elements as well as proteins involved in defense functions and cell motility are, on average, more variable than proteins with housekeeping functions. Additionally, using linear discriminant analysis, we found that variability and fraction of genomes carrying a given gene are the two variables that provide the best prediction of gene essentiality as compared to the results of transposon mutagenesis in Sulfolobus islandicus., Conclusions: Variability, a measure of sequence diversity within an alignment relative to the overall diversity within a group of organisms, offers a convenient proxy for evolutionary rate estimates and is informative with respect to prediction of functional properties of proteins. In particular, variability is a strong predictor of gene essentiality for the respective organisms and indicative of sub- or neofunctionalization of paralogs., (© 2022. The Author(s).)

Liquid-liquid phase separation (LLPS) forms biomolecular condensates or coacervates in cells. Metabolic enzymes can form phase-separated subcellular compartments that enrich enzymes, cofactors, and substrates. Herein, we report the construction of synthetic multienzyme condensates that catalyze the biosynthesis of a terpene, α-farnesene, in the prokaryote E. coli. RGGRGG derived from LAF-1 was used as the scaffold protein to form the condensates by LLPS. Multienzyme condensates were then formed by assembling two enzymes Idi and IspA through an RIAD/RIDD interaction. Multienzyme condensates constructed inside E. coli cells compartmentalized the cytosolic space into regions of high and low enzyme density and led to a significant enhancement of α-farnesene production. This work demonstrates LLPS-driven compartmentalization of the cytosolic space of prokaryotic cells, condensation of a biosynthetic pathway, and enhancement of the biosynthesis of α-farnesene., (© 2022 Wiley-VCH GmbH.)

Phylogenomic studies of prokaryotic taxa often assume conserved marker genes are homologous across their length. However, processes such as horizontal gene transfer or gene duplication and loss may disrupt this homology by recombining only parts of genes, causing gene fission or fusion. We show using simulation that it is necessary to delineate homology groups in a set of bacterial genomes without relying on gene annotations to define the boundaries of homologous regions. To solve this problem, we have developed a graph-based algorithm to partition a set of bacterial genomes into Maximal Homologous Groups of sequences (MHGs) where each MHG is a maximal set of maximum-length sequences which are homologous across the entire sequence alignment. We applied our algorithm to a dataset of 19 Enterobacteriaceae species and found that MHGs cover much greater proportions of genomes than markers and, relatedly, are less biased in terms of the functions of the genes they cover. We zoomed in on the correlation between each individual marker and their overlapping MHGs, and show that few phylogenetic splits supported by the markers are supported by the MHGs while many marker-supported splits are contradicted by the MHGs. A comparison of the species tree inferred from marker genes with the species tree inferred from MHGs suggests that the increased bias and lack of genome coverage by markers causes incorrect inferences as to the overall relationship between bacterial taxa., Competing Interests: The authors have declared that no competing interests exist.