Operons

Deciphering bacterial protein functions with innovative computational methods

Bacteria colonize every niche on Earth and play key roles in many environmental and host-associated processes. The sequencing revolution revealed the remarkable bacterial genetic and proteomic diversity and the genomic content of cultured and uncultured bacteria. However, deciphering functions of novel proteins remains a high barrier, often preventing the deep understanding of microbial life and its interaction with the surrounding environment. In recent years, exciting new bioinformatic tools, many of which are based on machine learning, facilitate the challenging task of gene and protein function discovery in the era of big genomics data, leading to the generation of testable hypotheses for bacterial protein functions. The new tools allow prediction of protein structures and interactions and allow sensitive and efficient sequence- and structure-based searching and clustering. Here, we summarize some of these recent tools which revolutionize modern microbiology research, along with examples for their usage, emphasizing the user-friendly, web-based ones. Adoption of these capabilities by experimentalists and computational biologists could save resources and accelerate microbiology research.

Synthetic translational coupling system for accurate and predictable polycistronic gene expression control in bacteria

Precise and predictable genetic elements are required to address various issues, such as suboptimal metabolic flux or imbalanced protein assembly caused by the inadequate control of polycistronic gene expression in bacteria. Here, we devised a synthetic biopart based on the translational coupling to control polycistronic gene expression. This module links the translation of genes within a polycistronic mRNA, maintaining their expression ratios regardless of coding sequences, transcription rate, and upstream gene translation rate. By engineering the Shine-Dalgarno sequences within these synthetic bioparts, we adjusted the expression ratios of polycistronic genes. We created 41 bioparts with varied relative expression ratios, ranging from 0.03 to 0.92, enabling precise control of pathway enzyme gene expression in a polycistronic manner. This led to up to a 7.6-fold increase in the production of valuable biochemicals such as 3-hydroxypropionic acid, poly(3-hydroxybutyrate), and lycopene. Our work provides genetic regulatory modules for precise and predictable polycistronic gene expression, facilitating efficient protein assembly, biosynthetic gene cluster expression, and pathway optimization.

Distribution of bacterial DNA repair proteins and their co-occurrence with immune systems

Bacteria encode various DNA repair pathways to maintain genome integrity. However, the high degree of homology between DNA repair proteins or their domains hampers accurate identification. Here, we describe a stringent search strategy to identify DNA repair proteins and provide a systematic analysis of taxonomic distribution and co-occurrence of DNA repair proteins involved in RecA-dependent homologous recombination. Our results reveal the widespread presence of RecA, SSB, and RecOR proteins and phyla-specific distribution for the DNA repair complexes RecBCD, AddAB, and AdnAB. Furthermore, we report co-occurrences of DNA repair proteins with immune systems, including specific CRISPR-Cas subtypes, prokaryotic Argonautes (pAgos), dGTPases, GAPS2, and Wadjet. Our results imply that while certain DNA repair proteins and immune systems might function in conjunction, no immune system strictly relies on a specific DNA repair protein. As such, these findings offer an updated perspective on the distribution of DNA repair systems and their connection to immune systems in bacteria.

A plasmid-chromosome crosstalk in multidrug resistant enterobacteria

Conjugative plasmids promote the dissemination and evolution of antimicrobial resistance in bacterial pathogens. However, plasmid acquisition can produce physiological alterations in the bacterial host, leading to potential fitness costs that determine the clinical success of bacteria-plasmid associations. In this study, we use a transcriptomic approach to characterize the interactions between a globally disseminated carbapenem resistance plasmid, pOXA-48, and a diverse collection of multidrug resistant (MDR) enterobacteria. Although pOXA-48 produces mostly strain-specific transcriptional alterations, it also leads to the common overexpression of a small chromosomal operon present in Klebsiella spp. and Citrobacter freundii strains. This operon includes two genes coding for a pirin and an isochorismatase family proteins (pfp and ifp), and shows evidence of horizontal mobilization across Proteobacteria species. Combining genetic engineering, transcriptomics, and CRISPRi gene silencing, we show that a pOXA-48-encoded LysR regulator is responsible for the plasmid-chromosome crosstalk. Crucially, the operon overexpression produces a fitness benefit in a pOXA-48-carrying MDR K. pneumoniae strain, suggesting that this crosstalk promotes the dissemination of carbapenem resistance in clinical settings.

Large-scale proteogenomics characterization of microproteins in Mycobacterium tuberculosis

Tuberculosis remains a burden to this day, due to the rise of multi and extensively drug-resistant bacterial strains. The genome of Mycobacterium tuberculosis (Mtb) strain H37Rv underwent an annotation process that excluded small Open Reading Frames (smORFs), which encode a class of peptides and small proteins collectively known as microproteins. As a result, there is an overlooked part of its proteome that is a rich source of potentially essential, druggable molecular targets. Here, we employed our recently developed proteogenomics pipeline to identify novel microproteins encoded by non-canonical smORFs in the genome of Mtb using hundreds of mass spectrometry experiments in a large-scale approach. We found protein evidence for hundreds of unannotated microproteins and identified smORFs essential for bacterial survival and involved in bacterial growth and virulence. Moreover, many smORFs are co-expressed and share operons with a myriad of biologically relevant genes and play a role in antibiotic response. Together, our data presents a resource of unknown genes that play a role in the success of Mtb as a widespread pathogen.

Accurate Identification of Periplasmic Urea-binding Proteins by Structure- and Genome Context-assisted Functional Analysis

ABC transporters are ancient and ubiquitous nutrient transport systems in bacteria and play a central role in defining lifestyles. Periplasmic solute-binding proteins (SBPs) are components that deliver ligands to their translocation machinery. SBPs have diversified to bind a wide range of ligands with high specificity and affinity. However, accurate assignment of cognate ligands remains a challenging problem in SBPs. Urea metabolism plays an important role in the nitrogen cycle; anthropogenic sources account for more than half of global nitrogen fertilizer. We report identification of urea-binding proteins within a large SBP sequence family that encodes diverse functions. By combining genetic linkage between SBPs, ABC transporter components, enzymes or transcription factors, we accurately identified cognate ligands, as we verified experimentally by biophysical characterization of ligand binding and crystallographic determination of the urea complex of a thermostable urea-binding homolog. Using three-dimensional structure information, these functional assignments were extrapolated to other members in the sequence family lacking genetic linkage information, which revealed that only a fraction bind urea. Using the same combined approaches, we also inferred that other family members bind various short-chain amides, aliphatic amino acids (leucine, isoleucine, valine), γ-aminobutyrate, and as yet unknown ligands. Comparative structural analysis revealed structural adaptations that encode diversification in these SBPs. Systematic assignment of ligands to SBP sequence families is key to understanding bacterial lifestyles, and also provides a rich source of biosensors for clinical and environmental analysis, such as the thermostable urea-binding protein identified here.

Essential Genes Discovery in Microorganisms by Transposon-Directed Sequencing (Tn-Seq): Experimental Approaches, Major Goals, and Future Perspectives

Essential genes are crucial for microbial viability, playing key roles in both the primary and secondary metabolism. Since mutations in these genes can threaten organism viability, identifying them is challenging. Conditionally essential genes are required only under specific conditions and are important for functions such as virulence, immunity, stress survival, and antibiotic resistance. Transposon-directed sequencing (Tn-Seq) has emerged as a powerful method for identifying both essential and conditionally essential genes. In this review, we explored Tn-Seq workflows, focusing on eubacterial species and some yeast species. A comparison of 14 eubacteria species revealed 133 conserved essential genes, including those involved in cell division (e.g., ftsA, ftsZ), DNA replication (e.g., dnaA, dnaE), ribosomal function, cell wall synthesis (e.g., murB, murC), and amino acid synthesis (e.g., alaS, argS). Many other essential genes lack clear orthologues across different microorganisms, making them specific to each organism studied. Conditionally essential genes were identified in 18 bacterial species grown under various conditions, but their conservation was low, reflecting dependence on specific environments and microorganisms. Advances in Tn-Seq are expected to reveal more essential genes in the near future, deepening our understanding of microbial biology and enhancing our ability to manipulate microbial growth, as well as both the primary and secondary metabolism.

Exploring the transcription start sites and other genomic features facilitates the accurate identification and annotation of small RNAs across multiple stress conditions in Mycobacterium tuberculosis

Mycobacterium tuberculosis (MTB) is a pathogen that is known for its ability to persist in harsh environments and cause chronic infections. Understanding the regulatory networks of MTB is crucial for developing effective treatments. Small regulatory RNAs (sRNAs) play important roles in gene expression regulation in all kingdoms of life, and their classification based solely on genomic location can be imprecise due to the computational-based prediction of protein-coding genes in bacteria, which often neglects segments of mRNA such as 5'UTRs, 3'UTRs, and intercistronic regions of operons. To address this issue, our study simultaneously discovered genomic features such as TSSs, UTRs, and operons together with sRNAs in the M. tuberculosis H37Rv strain (ATCC 27294) across multiple stress conditions. Our analysis identified 1,376 sRNA candidates and 8,173 TSSs in MTB, providing valuable insights into its complex regulatory landscape. TSS mapping enabled us to classify these sRNAs into more specific categories, including promoter-associated sRNAs, 5'UTR-derived sRNAs, 3'UTR-derived sRNAs, true intergenic sRNAs, and antisense sRNAs. Three of these sRNA candidates were experimentally validated using 3'-RACE-PCR: predictedRNA_0240, predictedRNA_0325, and predictedRNA_0578. Future characterization and validation are necessary to fully elucidate the functions and roles of these sRNAs in MTB. Our study is the first to simultaneously unravel TSSs and sRNAs in MTB and demonstrate that the identification of other genomic features, such as TSSs, UTRs, and operons, allows for more accurate and specific classification of sRNAs.

Expanding the synthetic biology repertoire of a fast-growing cyanobacterium Synechococcus elongatus PCC 11801

Synechococcus elongatus PCC 11801 is a fast-growing cyanobacterium, exhibiting high tolerance to environmental stresses. We have earlier characterized its genome and analysed its transcriptome and proteome. However, to deploy it as a potential cell factory, it is necessary to expand its synthetic biology toolbox, including promoter elements and ribosome binding sites (RBSs). Here, based on the global transcriptome analysis, 48 native promoters of the genes with high transcript count were characterized using a fluorescent reporter system. The promoters PcpcB, PpsbA1, and P11770 exhibited consistently high fluorescence under all the cultivation conditions. Similarly, from the genome data and proteome analysis, 534 operons were identified. Fifteen intergenic regions exhibiting higher protein expression from the downstream gene were systematically characterized for identifying RBSs, using an operon construct comprising fluorescent protein genes eyfp and mTurq under PcpcB (PcpcB:eyfp:RBS:mTurq:TrrnB). Overall, the work presents promoter and RBS sequence libraries, with varying strengths, to expedite bioengineering of PCC 11801.

The Y-ome Conundrum: Insights into Uncharacterized Genes and Approaches for Functional Annotation

The ever-increasing availability of genome sequencing data has revealed a substantial number of uncharacterized genes without known functions across various organisms. The first comprehensive genome sequencing of E. coli K12 revealed that more than 50% of its open reading frames corresponded to transcripts with no known functions. The group of protein-coding genes without a functional description and/or a recognized pathway, beginning with the letter "Y", is classified as the "y-ome". Several efforts have been made to elucidate the functions of these genes and to recognize their role in biological processes. This review provides a brief update on various strategies employed when studying the y-ome, such as high-throughput experimental approaches, comparative omics, metabolic engineering, gene expression analysis, and data integration techniques. Additionally, we highlight recent advancements in functional annotation methods, including the use of machine learning, network analysis, and functional genomics approaches. Novel approaches are required to produce more precise functional annotations across the genome to reduce the number of genes with unknown functions.

Large-scale investigation of species-specific orphan genes in the human gut microbiome elucidates their evolutionary origins

Species-specific genes, also known as orphans, are ubiquitous across life's domains. In prokaryotes, species-specific orphan genes (SSOGs) are mostly thought to originate in external elements such as viruses followed by horizontal gene transfer, whereas the scenario of native origination, through rapid divergence or de novo, is mostly dismissed. However, quantitative evidence supporting either scenario is lacking. Here, we systematically analyzed genomes from 4644 human gut microbiome species and identified more than 600,000 unique SSOGs, representing an average of 2.6% of a given species' pangenome. These sequences are mostly rare within each species yet show signs of purifying selection. Overall, SSOGs use optimal codons less frequently, and their proteins are more disordered than those of conserved genes (i.e., non-SSOGs). Importantly, across species, the GC content of SSOGs closely matches that of conserved ones. In contrast, the ∼5% of SSOGs that share similarity to known viral sequences have distinct characteristics, including lower GC content. Thus, SSOGs with similarity to viruses differ from the remaining SSOGs, contrasting an external origination scenario for most of them. By examining the orthologous genomic region in closely related species, we show that a small subset of SSOGs likely evolved natively de novo and find that these genes also differ in their properties from the remaining SSOGs. Our results challenge the notion that external elements are the dominant source of prokaryotic genetic novelty and will enable future studies into the biological role and relevance of species-specific genes in the human gut.

Adaptation of a fluoroquinolone-sensitive Shigella sonnei to norfloxacin exposure

Shigella causes shigellosis that requires antibiotic treatment in severe cases. Sublethal antibiotic concentrations can promote resistance, but their effect on antibiotic-sensitive bacteria before resistance development is unclear. This study investigated the effects of sublethal norfloxacin (NOR) challenges on a NOR-sensitive strain, Shigella sonnei UKMCC1015. Firstly, the whole genome of S. sonnei UKMCC1015 was assembled, and 45 antimicrobial resistance (AMR) genes were identified. Interestingly, transcriptomic analysis showed that low NOR levels do not change either the expression of the AMR genes or NOR targets such as gyrA. Instead, multiple ribosomal protein genes were downregulated, which could be attributed to decreased ribosomal protein promoter activity, modulated by elevated guanosine pentaphosphate and tetraphosphate (ppGpp) levels. This alarmone is involved in the bacterial stringent response during environmental stress, and it is mainly produced from the ppGpp synthetase (relA). Additionally, we observed that a relA overexpression (prolonged period of elevated ppGpp levels) may negatively affect the NOR tolerance of the bacteria. In conclusion, this study revealed that a NOR-sensitive strain responds differently to sublethal NOR than commonly reported in resistant strains.

Heliorhodopsin-mediated light-modulation of ABC transporter

Heliorhodopsins (HeRs) have been hypothesized to have widespread functions. Recently, the functions for few HeRs have been revealed; however, the hypothetical functions remain largely unknown. Herein, we investigate light-modulation of heterodimeric multidrug resistance ATP-binding cassette transporters (OmrDE) mediated by Omithinimicrobium cerasi HeR. In this study, we classifiy genes flanking the HeR-encoding genes and identify highly conservative residues for protein-protein interactions. Our results reveal that the interaction between OcHeR and OmrDE shows positive cooperatively sequential binding through thermodynamic parameters. Moreover, light-induced OcHeR upregulates OmrDE drug transportation. Hence, the binding may be crucial to drug resistance in O. cerasi as it survives in a drug-containing habitat. Overall, we unveil a function of HeR as regulatory rhodopsin for multidrug resistance. Our findings suggest potential applications in optogenetic technology.

Phylogenomics of the psychoactive mushroom genus Psilocybe and evolution of the psilocybin biosynthetic gene cluster

Psychoactive mushrooms in the genus Psilocybe have immense cultural value and have been used for centuries in Mesoamerica. Despite the recent surge of interest in these mushrooms due to the psychotherapeutic potential of their natural alkaloid psilocybin, their phylogeny and taxonomy remain substantially incomplete. Moreover, the recent elucidation of the psilocybin biosynthetic gene cluster is known for only five of ~165 species of Psilocybe, four of which belong to only one of two major clades. We set out to improve the phylogeny of Psilocybe using shotgun sequencing of fungarium specimens, from which we obtained 71 metagenomes including from 23 types, and conducting phylogenomic analysis of 2,983 single-copy gene families to generate a fully supported phylogeny. Molecular clock analysis suggests the stem lineage of Psilocybe arose ~67 mya and diversified ~56 mya. We also show that psilocybin biosynthesis first arose in Psilocybe, with 4 to 5 possible horizontal transfers to other mushrooms between 40 and 9 mya. Moreover, predicted orthologs of the psilocybin biosynthetic genes revealed two distinct gene orders within the biosynthetic gene cluster that corresponds to a deep split within the genus, possibly a signature of two independent acquisitions of the cluster within Psilocybe.

Comparative genomics sheds light on transcription factor-mediated regulation in the extreme acidophilic Acidithiobacillia representatives

Extreme acidophiles thrive in acidic environments, confront a multitude of challenges, and demonstrate remarkable adaptability in their metabolism to cope with the ever-changing environmental fluctuations, which encompass variations in temperature, pH levels, and the availability of electron acceptors and donors. The survival and proliferation of members within the Acidithiobacillia class rely on the deployment of transcriptional regulatory systems linked to essential physiological traits. The study of these transcriptional regulatory systems provides valuable insights into critical processes, such as energy metabolism and nutrient assimilation, and how they integrate into major genetic-metabolic circuits. In this study, we examined the transcriptional regulatory repertoires and potential interactions of forty-three Acidithiobacillia complete and draft genomes, encompassing nine species. To investigate the function and diversity of Transcription Factors (TFs) and their DNA Binding Sites (DBSs), we conducted a genome-wide comparative analysis, which allowed us to identify these regulatory elements in representatives of Acidithiobacillia. We classified TFs into gene families and compared their occurrence among all representatives, revealing conservation patterns across the class. The results identified conserved regulators for several pathways, including iron and sulfur oxidation, the main pathways for energy acquisition, providing new evidence for viable regulatory interactions and branch-specific conservation in Acidithiobacillia. The identification of TFs and DBSs not only corroborates existing experimental information for selected species, but also introduces novel candidates for experimental validation. Moreover, these promising candidates have the potential for further extension to new representatives within the class.

The protein interactome of the citrus Huanglongbing pathogen Candidatus Liberibacter asiaticus

The bacterium Candidatus Liberibacter asiaticus (CLas) causes citrus Huanglongbing disease. Our understanding of the pathogenicity and biology of this microorganism remains limited because CLas has not yet been cultivated in artificial media. Its genome is relatively small and encodes approximately 1136 proteins, of which 415 have unknown functions. Here, we use a high-throughput yeast-two-hybrid (Y2H) screen to identify interactions between CLas proteins, thus providing insights into their potential functions. We identify 4245 interactions between 542 proteins, after screening 916 bait and 936 prey proteins. The false positive rate of the Y2H assay is estimated to be 2.9%. Pull-down assays for nine protein-protein interactions (PPIs) likely involved in flagellar function support the robustness of the Y2H results. The average number of PPIs per node in the CLas interactome is 15.6, which is higher than the numbers previously reported for interactomes of free-living bacteria, suggesting that CLas genome reduction has been accompanied by increased protein multi-functionality. We propose potential functions for 171 uncharacterized proteins, based on the PPI results, guilt-by-association analyses, and comparison with data from other bacterial species. We identify 40 hub-node proteins, including quinone oxidoreductase and LysR, which are known to protect other bacteria against oxidative stress and might be important for CLas survival in the phloem. We expect our PPI database to facilitate research on CLas biology and pathogenicity mechanisms.

Two-Omics Probe on the Potential of Pseudomonas sp. GDMCC 1.1703 Under Phenol Stress

Pseudomonas sp. harbors genetic diversity and readily adapts to environmental challenges, conferring upon it the ability to remediate. It is important to genetically determine the effects of bacterial application. The two-omics integration approach may shed more light on Pseudomonas isolates, filling the knowledge gap between genetic potential and dynamic function. In the present study, a strain from the Xi River was isolated using benzene-selective enrichment medium and phylogenetically identified as Pseudomonas sp. GDMCC 1.1703 by 16S rRNA gene sequencing. Its phenol degradability was optimally assessed at a rate of 45.7% (by statistics P < 0.05) in 12 h with a 200 mg/L concentration. Genomics and transcriptomics analyses were successively used to identify the genes and pathways responsible for phenol degradation. At least 42 genes were genomically identified to be involved in xenobiotic biodegradation. The degradative genes clustered into operons were hypothesized to have evolved through horizontal gene transfer. On the basis of genomic authentication, transcriptome analysis dynamically revealed that phenol degradation and responsive mechanisms were both upregulated as defense between the Ctrl (control) and PS (phenol-stressed) groups. Quantitative reverse transcription-PCR not only validated the key genes identified via RNA sequencing but also consistently confirmed the realistic intracellular expression. The approach of omics integration, which is effective in exploring the potential of isolates, will hopefully become an established method for determining the remediation potential of a candidate for development.

Ribosomal Protein Cluster Organization in Asgard Archaea

It has been proposed that the superphylum of Asgard Archaea may represent a historical link between the Archaea and Eukarya. Following the discovery of the Archaea, it was soon appreciated that archaeal ribosomes were more similar to those of Eukarya rather than Bacteria. Coupled with other eukaryotic-like features, it has been suggested that the Asgard Archaea may be directly linked to eukaryotes. However, the genomes of Bacteria and non-Asgard Archaea generally organize ribosome-related genes into clusters that likely function as operons. In contrast, eukaryotes typically do not employ an operon strategy. To gain further insight into conservation of the r-protein genes, the genome order of conserved ribosomal protein (r-protein) coding genes was identified in 17 Asgard genomes (thirteen complete genomes and four genomes with less than 20 contigs) and compared with those found previously in non-Asgard archaeal and bacterial genomes. A universal core of two clusters of 14 and 4 cooccurring r-proteins, respectively, was identified in both the Asgard and non-Asgard Archaea. The equivalent genes in the E. coli version of the cluster are found in the S10 and spc operons. The large cluster of 14 r-protein genes (uS19-uL22-uS3-uL29-uS17 from the S10 operon and uL14-uL24-uL5-uS14-uS8-uL6-uL18-uS5-uL30-uL15 from the spc operon) occurs as a complete set in the genomes of thirteen Asgard genomes (five Lokiarchaeotes, three Heimdallarchaeotes, one Odinarchaeote, and four Thorarchaeotes). Four less conserved clusters with partial bacterial equivalents were found in the Asgard. These were the L30e (str operon in Bacteria) cluster, the L18e (alpha operon in Bacteria) cluster, the S24e-S27ae-rpoE1 cluster, and the L31e, L12..L1 cluster. Finally, a new cluster referred to as L7ae was identified. In many cases, r-protein gene clusters/operons are less conserved in their organization in the Asgard group than in other Archaea. If this is generally true for nonribosomal gene clusters, the results may have implications for the history of genome organization. In particular, there may have been an early transition to or from the operon approach to genome organization. Other nonribosomal cellular features may support different relationships. For this reason, it may be important to consider ribosome features separately.

Prokaryotic membrane coat - like proteins: An update

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.

Protein family neighborhood analyzer-ProFaNA

Background

Functionally related genes are well known to be often grouped in close vicinity in the genomes, particularly in prokaryotes. Notwithstanding the diverse evolutionary mechanisms leading to this phenomenon, it can be used to predict functions of uncharacterized genes.

Methods

Here, we provide a simple but robust statistical approach that leverages the vast amounts of genomic data available today. Considering a protein domain as a functional unit, one can explore other functional units (domains) that significantly often occur within the genomic neighborhoods of the queried domain. This analysis can be performed across different taxonomic levels. Provisions can also be made to correct for the uneven sampling of the taxonomic space by genomic sequencing projects that often focus on large numbers of very closely related strains, e.g., pathogenic ones. To this end, an optional procedure for averaging occurrences within subtaxa is available.

Results

Several examples show this approach can provide useful functional predictions for uncharacterized gene families, and how to combine this information with other approaches. The method is made available as a web server at http://bioinfo.sggw.edu.pl/neighborhood_analysis.

Endophytic fungi: hidden treasure chest of antimicrobial metabolites interrelationship of endophytes and metabolites

Endophytic fungi comprise host-associated fungal communities which thrive within the tissues of host plants and produce a diverse range of secondary metabolites with various bioactive attributes. The metabolites such as phenols, polyketides, saponins, alkaloids help to mitigate biotic and abiotic stresses, fight against pathogen attacks and enhance the plant immune system. We present an overview of the association of endophytic fungal communities with a plant host and discuss molecular mechanisms induced during their symbiotic interaction. The overview focuses on the secondary metabolites (especially those of terpenoid nature) secreted by endophytic fungi and their respective function. The recent advancement in multi-omics approaches paved the way for identification of these metabolites and their characterization via comparative analysis of extensive omics datasets. This study also elaborates on the role of diverse endophytic fungi associated with key agricultural crops and hence important for sustainability of agriculture.

Bioinformatics of cyanophycin metabolism genes and characterization of promiscuous isoaspartyl dipeptidases that catalyze the final step of cyanophycin degradation

Cyanophycin is a bacterial biopolymer used for storage of fixed nitrogen. It is composed of a backbone of L-aspartate residues with L-arginines attached to each of their side chains. Cyanophycin is produced by cyanophycin synthetase 1 (CphA1) using Arg, Asp and ATP, and is degraded in two steps. First, cyanophycinase breaks down the backbone peptide bonds, releasing β-Asp-Arg dipeptides. Then, these dipeptides are broken down into free Asp and Arg by enzymes with isoaspartyl dipeptidase activity. Two bacterial enzymes are known to possess promiscuous isoaspartyl dipeptidase activity: isoaspartyl dipeptidase (IadA) and isoaspartyl aminopeptidase (IaaA). We performed a bioinformatic analysis to investigate whether genes for cyanophycin metabolism enzymes cluster together or are spread around the microbial genomes. Many genomes showed incomplete contingents of known cyanophycin metabolizing genes, with different patterns in various bacterial clades. Cyanophycin synthetase and cyanophycinase are usually clustered together when recognizable genes for each are found within a genome. Cyanophycinase and isoaspartyl dipeptidase genes typically cluster within genomes lacking cphA1. About one-third of genomes with genes for CphA1, cyanophycinase and IaaA show these genes clustered together, while the proportion is around one-sixth for CphA1, cyanophycinase and IadA. We used X-ray crystallography and biochemical studies to characterize an IadA and an IaaA from two such clusters, in Leucothrix mucor and Roseivivax halodurans, respectively. The enzymes retained their promiscuous nature, showing that being associated with cyanophycin-related genes did not make them specific for β-Asp-Arg dipeptides derived from cyanophycin degradation.

Can molecular dynamics be used to simulate biomolecular recognition?

There are many problems in biochemistry that are difficult to study experimentally. Simulation methods are appealing due to direct availability of atomic coordinates as a function of time. However, direct molecular simulations are challenged by the size of systems and the time scales needed to describe relevant motions. In theory, enhanced sampling algorithms can help to overcome some of the limitations of molecular simulations. Here, we discuss a problem in biochemistry that offers a significant challenge for enhanced sampling methods and that could, therefore, serve as a benchmark for comparing approaches that use machine learning to find suitable collective variables. In particular, we study the transitions LacI undergoes upon moving between being non-specifically and specifically bound to DNA. Many degrees of freedom change during this transition and that the transition does not occur reversibly in simulations if only a subset of these degrees of freedom are biased. We also explain why this problem is so important to biologists and the transformative impact that a simulation of it would have on the understanding of DNA regulation.

Functional Clustering of Metabolically Related Genes Is Conserved across Dikarya

Transcriptional regulation is vital for organismal survival, with many layers and mechanisms collaborating to balance gene expression. One layer of this regulation is genome organization, specifically the clustering of functionally related, co-expressed genes along the chromosomes. Spatial organization allows for position effects to stabilize RNA expression and balance transcription, which can be advantageous for a number of reasons, including reductions in stochastic influences between the gene products. The organization of co-regulated gene families into functional clusters occurs extensively in Ascomycota fungi. However, this is less characterized within the related Basidiomycota fungi despite the many uses and applications for the species within this clade. This review will provide insight into the prevalence, purpose, and significance of the clustering of functionally related genes across Dikarya, including foundational studies from Ascomycetes and the current state of our understanding throughout representative Basidiomycete species.

The Operon as a Conundrum of Gene Dynamics and Biochemical Constraints: What We Have Learned from Histidine Biosynthesis

Operons represent one of the leading strategies of gene organization in prokaryotes, having a crucial influence on the regulation of gene expression and on bacterial chromosome organization. However, there is no consensus yet on why, how, and when operons are formed and conserved, and many different theories have been proposed. Histidine biosynthesis is a highly studied metabolic pathway, and many of the models suggested to explain operons origin and evolution can be applied to the histidine pathway, making this route an attractive model for the study of operon evolution. Indeed, the organization of his genes in operons can be due to a progressive clustering of biosynthetic genes during evolution, coupled with a horizontal transfer of these gene clusters. The necessity of physical interactions among the His enzymes could also have had a role in favoring gene closeness, of particular importance in extreme environmental conditions. In addition, the presence in this pathway of paralogous genes, heterodimeric enzymes and complex regulatory networks also support other operon evolution hypotheses. It is possible that histidine biosynthesis, and in general all bacterial operons, may result from a mixture of several models, being shaped by different forces and mechanisms during evolution.

Target enrichment of long open reading frames and ultraconserved elements to link microevolution and macroevolution in non-model organisms

Despite the increasing accessibility of high-throughput sequencing, obtaining high-quality genomic data on non-model organisms without proximate well-assembled and annotated genomes remains challenging. Here, we describe a workflow that takes advantage of distant genomic resources and ingroup transcriptomes to select and jointly enrich long open reading frames (ORFs) and ultraconserved elements (UCEs) from genomic samples for integrative studies of microevolutionary and macroevolutionary dynamics. This workflow is applied to samples of the African unionid bivalve tribe Coelaturini (Parreysiinae) at basin and continent-wide scales. Our results indicate that ORFs are efficiently captured without prior identification of intron-exon boundaries. The enrichment of UCEs was less successful, but nevertheless produced substantial data sets. Exploratory continent-wide phylogenetic analyses with ORF supercontigs (>515,000 parsimony informative sites) resulted in a fully resolved phylogeny, the backbone of which was also retrieved with UCEs (>11,000 informative sites). Variant calling on ORFs and UCEs of Coelaturini from the Malawi Basin produced ~2000 SNPs per population pair. Estimates of nucleotide diversity and population differentiation were similar for ORFs and UCEs. They were low compared to previous estimates in molluscs, but comparable to those in recently diversifying Malawi cichlids and other taxa at an early stage of speciation. Skimming off-target sequence data from the same enriched libraries of Coelaturini from the Malawi Basin, we reconstructed the maternally-inherited mitogenome, which displays the gene order inferred for the most recent common ancestor of Unionidae. Overall, our workflow and results provide exciting perspectives for integrative genomic studies of microevolutionary and macroevolutionary dynamics in non-model organisms.

Three Novel Antisense Overlapping Genes in E. coli O157:H7 EDL933

The abundance of long overlapping genes in prokaryotic genomes is likely to be significantly underestimated. To date, only a few examples of such genes are fully established. Using RNA sequencing and ribosome profiling, we found expression of novel overlapping open reading frames in Escherichia coli O157:H7 EDL933 (EHEC). Indeed, the overlapping candidate genes are equipped with typical structural elements required for transcription and translation, i.e., promoters, transcription start sites, as well as terminators, all of which were experimentally verified. Translationally arrested mutants, unable to produce the overlapping encoded protein, were found to have a growth disadvantage when grown competitively against the wild type. Thus, the phenotypes found imply biological functionality of the genes at the level of proteins produced. The addition of 3 more examples of prokaryotic overlapping genes to the currently limited, yet constantly growing pool of such genes emphasizes the underestimated coding capacity of bacterial genomes. IMPORTANCE The abundance of long overlapping genes in prokaryotic genomes is likely to be significantly underestimated, since such genes are not allowed in genome annotations. However, ribosome profiling catches mRNA in the moment of being template for protein production. Using this technique and subsequent experiments, we verified 3 novel overlapping genes encoded in antisense of known genes. This adds more examples of prokaryotic overlapping genes to the currently limited, yet constantly growing pool of such genes.

Oxidative Fermentation of Acetic Acid Bacteria and Its Products

Acetic acid bacteria (AAB) are a group of Gram-negative, strictly aerobic bacteria, including 19 reported genera until 2021, which are widely found on the surface of flowers and fruits, or in traditionally fermented products. Many AAB strains have the great abilities to incompletely oxidize a large variety of carbohydrates, alcohols and related compounds to the corresponding products mainly including acetic acid, gluconic acid, gulonic acid, galactonic acid, sorbose, dihydroxyacetone and miglitol via the membrane-binding dehydrogenases, which is termed as AAB oxidative fermentation (AOF). Up to now, at least 86 AOF products have been reported in the literatures, but no any monograph or review of them has been published. In this review, at first, we briefly introduce the classification progress of AAB due to the rapid changes of AAB classification in recent years, then systematically describe the enzymes involved in AOF and classify the AOF products. Finally, we summarize the application of molecular biology technologies in AOF researches.

System Principles Governing the Organization, Architecture, Dynamics, and Evolution of Gene Regulatory Networks

Synthetic biology aims to apply engineering principles for the rational, systematical design and construction of biological systems displaying functions that do not exist in nature or even building a cell from scratch. Understanding how molecular entities interconnect, work, and evolve in an organism is pivotal to this aim. Here, we summarize and discuss some historical organizing principles identified in bacterial gene regulatory networks. We propose a new layer, the concilion, which is the group of structural genes and their local regulators responsible for a single function that, organized hierarchically, coordinate a response in a way reminiscent of the deliberation and negotiation that take place in a council. We then highlight the importance that the network structure has, and discuss that the natural decomposition approach has unveiled the system-level elements shaping a common functional architecture governing bacterial regulatory networks. We discuss the incompleteness of gene regulatory networks and the need for network inference and benchmarking standardization. We point out the importance that using the network structural properties showed to improve network inference. We discuss the advances and controversies regarding the consistency between reconstructions of regulatory networks and expression data. We then discuss some perspectives on the necessity of studying regulatory networks, considering the interactions’ strength distribution, the challenges to studying these interactions’ strength, and the corresponding effects on network structure and dynamics. Finally, we explore the ability of evolutionary systems biology studies to provide insights into how evolution shapes functional architecture despite the high evolutionary plasticity of regulatory networks.

Differential synthesis of novel small protein times Salmonella virulence program

Gene organization in operons enables concerted transcription of functionally related genes and efficient control of cellular processes. Typically, an operon is transcribed as a polycistronic mRNA that is translated into corresponding proteins. Here, we identify a bicistronic operon transcribed as two mRNAs, yet only one allows translation of both genes. We establish that the novel gene ugtS forms an operon with virulence gene ugtL, an activator of the master virulence regulatory system PhoP/PhoQ in Salmonella enterica serovar Typhimurium. Only the longer ugtSugtL mRNA carries the ugtS ribosome binding site and therefore allows ugtS translation. Inside macrophages, the ugtSugtL mRNA species allowing translation of both genes is produced hours before that allowing translation solely of ugtL. The small protein UgtS controls the kinetics of PhoP phosphorylation by antagonizing UgtL activity, preventing premature activation of a critical virulence program. Moreover, S. enterica serovars that infect cold-blooded animals lack ugtS. Our results establish how foreign gene control of ancestral regulators enables pathogens to time their virulence programs.

Pathogens must express their virulence genes at precisely the right time to cause disease. Here, we identify a novel small protein that governs a critical virulence program in the pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium). We establish that the novel small protein UgtS prevents the virulence protein UgtL from activating the master virulence regulator PhoP inside macrophages. S. Typhimurium produces two ugtSugtL mRNAs, but only one of them allows ugtS translation. The absence of ugtS from S. enterica serovars that infect cold-blooded animals raises the possibility of UgtS playing a regulatory role during infection of warm-blooded animals. Our findings establish how a horizontally acquired bicistron enables pathogens to time their virulence programs by controlling ancestral regulators.

Molecular biology: Fantastic toolkits to improve knowledge and application of acetic acid bacteria

Acetic acid bacteria (AAB) are a group of gram-negative, obligate aerobic bacteria within the Acetobacteraceae family of the alphaproteobacteria class, which are distributed in a wide variety of different natural sources that are rich in sugar and alcohols, as well as in several traditionally fermented foods. Their capabilities are not limited to the production of acetic acid and the brewing of vinegar, as their names suggest. They can also fix nitrogen and produce various kinds of aldehydes, ketones and other organic acids by incomplete oxidation (also referred to as oxidative fermentation) of the corresponding alcohols and/or sugars, as well as pigments and exopolysaccharides (EPS). In order to gain more insight into these organisms, molecular biology techniques have been extensively applied in almost all aspects of AAB research, including their identification and classification, acid resistance mechanisms, oxidative fermentation, EPS production, thermotolerance and so on. In this review, we mainly focus on the application of molecular biological technologies in the advancement of research into AAB while presenting the progress of the latest studies using these techniques.

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high recall or high specificity. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded as additional data is generated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility, and adaptability.

Bacteria and archaea, single-cell organisms collectively known as prokaryotes, live in all imaginable environments and comprise the majority of living organisms on this planet. Prokaryotes play a critical role in the homeostasis of multicellular organisms (such as animals and plants) and ecosystems. In addition, bacteria can be pathogenic and cause a variety of diseases in these same hosts and ecosystems. In short, understanding the biology and molecular functions of bacteria and archaea and devising mechanisms to engineer and optimize their properties are critical scientific endeavors with significant implications in healthcare, agriculture, manufacturing, and climate science among others. One major molecular difference between unicellular and multicellular organisms is the way they express genes–multicellular organisms make individual RNA molecules for each gene while, prokaryotes express operons (i.e., a group of genes coding functionally related proteins) in contiguous polycistronic RNA molecules. Understanding which genes exist within operons is critical for elucidating basic biology and for engineering organisms. In this work, we use a combination of statistical and machine learning-based methods to use next-generation sequencing data to predict operon structure across a range of prokaryotes. Our method provides an easily implemented, robust, accurate, and flexible way to determine operon structure in an organism-agnostic manner using readily available data.

Overlapping genes in natural and engineered genomes

Modern genome-scale methods that identify new genes, such as proteogenomics and ribosome profiling, have revealed, to the surprise of many, that overlap in genes, open reading frames and even coding sequences is widespread and functionally integrated into prokaryotic, eukaryotic and viral genomes. In parallel, the constraints that overlapping regions place on genome sequences and their evolution can be harnessed in bioengineering to build more robust synthetic strains and constructs. With a focus on overlapping protein-coding and RNA-coding genes, this Review examines their discovery, topology and biogenesis in the context of their genome biology. We highlight exciting new uses for sequence overlap to control translation, compress synthetic genetic constructs, and protect against mutation.

Current and emerging tools of computational biology to improve the detoxification of mycotoxins

Biological organisms carry a rich potential for removing toxins from our environment, but identifying suitable candidates and improving them remain challenging. We explore the use of computational tools to discover strains and enzymes that detoxify harmful compounds. In particular, we will focus on mycotoxins-fungi-produced toxins that contaminate food and feed-and biological enzymes that are capable of rendering them less harmful. We discuss the use of established and novel computational tools to complement existing empirical data in three directions: discovering the prospect of detoxification among underexplored organisms, finding important cellular processes that contribute to detoxification, and improving the performance of detoxifying enzymes. We hope to create a synergistic conversation between researchers in computational biology and those in the bioremediation field. We showcase open bioremediation questions where computational researchers can contribute and highlight relevant existing and emerging computational tools that could benefit bioremediation researchers.

Internal Promoters and Their Effects on the Transcription of Operon Genes for Epothilone Production in Myxococcus xanthus

The biosynthetic genes for secondary metabolites are often clustered into giant operons with no transcription terminator before the end. The long transcripts are frangible and the transcription efficiency declines along with the process. Internal promoters might occur in operons to coordinate the transcription of individual genes, but their effects on the transcription of operon genes and the yield of metabolites have been less investigated. Epothilones are a kind of antitumor polyketides synthesized by seven multifunctional enzymes encoded by a 56-kb operon. In this study, we identified multiple internal promoters in the epothilone operon. We performed CRISPR-dCas9–mediated transcription activation of internal promoters, combined activation of different promoters, and activation in different epothilone-producing M. xanthus strains. We found that activation of internal promoters in the operon was able to promote the gene transcription, but the activation efficiency was distinct from the activation of separate promoters. The transcription of genes in the operon was influenced by not only the starting promoter but also internal promoters of the operon; internal promoters affected the transcription of the following and neighboring upstream/downstream genes. Multiple interferences between internal promoters thus changed the transcriptional profile of operon genes and the production of epothilones. Better activation efficiency for the gene transcription and the epothilone production was obtained in the low epothilone-producing strains. Our results highlight that interactions between promoters in the operon are critical for the gene transcription and the metabolite production efficiency.

PLAZA 5.0: extending the scope and power of comparative and functional genomics in plants

PLAZA is a platform for comparative, evolutionary, and functional plant genomics. It makes a broad set of genomes, data types and analysis tools available to researchers through a user-friendly website, an API, and bulk downloads. In this latest release of the PLAZA platform, we are integrating a record number of 134 high-quality plant genomes, split up over two instances: PLAZA Dicots 5.0 and PLAZA Monocots 5.0. This number of genomes corresponds with a massive expansion in the number of available species when compared to PLAZA 4.0, which offered access to 71 species, a 89% overall increase. The PLAZA 5.0 release contains information for 5 882 730 genes, and offers pre-computed gene families and phylogenetic trees for 5 274 684 protein-coding genes. This latest release also comes with a set of new and updated features: a new BED import functionality for the workbench, improved interactive visualizations for functional enrichments and genome-wide mapping of gene sets, and a fully redesigned and extended API. Taken together, this new version offers extended support for plant biologists working on different families within the green plant lineage and provides an efficient and versatile toolbox for plant genomics. All PLAZA releases are accessible from the portal website: https://bioinformatics.psb.ugent.be/plaza/.

A large-scale genomic association analysis identifies a fragment in Dt11 chromosome conferring cotton Verticillium wilt resistance

Verticillium wilt (VW) is a destructive disease that results in great losses in cotton yield and quality. Identifying genetic variation that enhances crop disease resistance is a primary objective in plant breeding. Here we reported a GWAS of cotton VW resistance in a natural-variation population, challenged by different pathogenicity stains and different environments, and found 382 SNPs significantly associated with VW resistance. The associated signal repeatedly peaked in chromosome Dt11 (68 798 494-69 212 808) containing 13 core elite alleles undescribed previously. The core SNPs can make the disease reaction type from susceptible to tolerant or resistant in accessions with alternate genotype compared to reference genotype. Of the genes associated with the Dt11 signal, 25 genes differentially expressed upon Verticillium dahliae stress, with 21 genes verified in VW resistance via gene knockdown and/or overexpression experiments. We firstly discovered that a gene cluster of L-type lectin-domain containing receptor kinase (GhLecRKs-V.9) played an important role in VW resistance. These results proved that the associated Dt11 region was a major genetic locus responsible for VW resistance. The frequency of the core elite alleles (FEA) in modern varieties was significantly higher than the early/middle varieties (12.55% vs 4.29%), indicating that the FEA increased during artificial selection breeding. The current developmental resistant cultivars, JND23 and JND24, had fixed these core elite alleles during breeding without yield penalty. These findings unprecedentedly provided genomic variations and promising alleles for promoting cotton VW resistance improvement.

Pectobacterium parmentieri SCC 3193 Mutants with Altered Synthesis of Cell Surface Polysaccharides Are Resistant to N4-Like Lytic Bacteriophage ϕA38 (vB_Ppp_A38) but Express Decreased Virulence in Potato (Solanum tuberosum L.) Plants

Pectobacterium parmentieri is a Gram-negative plant-pathogenic bacterium able to infect potato (Solanum tuberosum L.). Little is known about lytic bacteriophages infecting P. parmentieri and how phage-resistance influences the environmental fitness and virulence of this species. A lytic phage vB_Ppp_A38 (ϕA38) has been previously isolated and characterized as a potential biological control agent for the management of P. parmentieri. In this study, seven P. parmentieri SCC 3193 Tn5 mutants were identified that exhibited resistance to infection caused by vB_Ppp_A38 (ϕA38). The genes disrupted in these seven mutants encoded proteins involved in the assembly of O-antigen, sugar metabolism, and the production of bacterial capsule exopolysaccharides. The potential of A38-resistant P. parmentieri mutants for plant colonization and pathogenicity as well as other phenotypes expected to contribute to the ecological fitness of P. parmentieri, including growth rate, use of carbon and nitrogen sources, production of pectinolytic enzymes, proteases, cellulases, and siderophores, swimming and swarming motility, presence of capsule and flagella as well as the ability to form biofilm were assessed. Compared to the wild-type P. parmentieri strain, all phage-resistant mutants exhibited a reduced ability to colonize and to cause symptoms in growing potato (S. tuberosum L.) plants. The implications of bacteriophage resistance on the ecological fitness of P. parmentieri are discussed.

Leveraging Microbial Genomes and Genomic Context for Chemical Discovery

The genomic era has dramatically changed how we discover and investigate microbial biochemistry. In particular, the exponential expansion in the number of sequenced microbial genomes provides investigators with a vast wealth of sequence data to exploit for the discovery of biochemical functions and mechanisms, as well as novel enzymes and metabolites. In contrast to early biochemical work, which was largely characterized by “forward” approaches that proceed from biomass to enzyme to gene, the availability of genome sequences enables the discovery of new microbial metabolic activities, enzymes, and metabolites by “reverse” approaches that originate with genetic information or by approaches that incorporate features of both forward and reverse methodologies. In the genomic era, the canonical organization of microbial genomes into gene clusters presents a singular opportunity for the utilization of genomic data. Specifically, genomic context (information gleaned from the genes surrounding a gene of interest in the chromosome) is a powerful tool for chemical discovery in microbial systems because of the functional and/or physiological relationship that usually exists between genes found within a gene cluster. This means that the investigator can use this inferred link to generate hypotheses about the functions of individual genes in the cluster or even the function of the entire cluster itself. Here, we discuss how analysis of genomic context in combination with a mechanistic understanding of enzymes can facilitate numerous facets of microbial biochemical research including the identification of biosynthetic gene clusters, the discovery of important and novel enzymes, the elucidation of natural product structures, and the identification of new metabolic pathways. We highlight work from our laboratory using genomic context to discover and study biosynthetic pathways that produce natural products, including the cylindrocyclophanes, nitrogen–nitrogen bond-containing metabolites, and the gut microbial genotoxin colibactin. Although use of genomic context is most commonly associated with studies of natural product biosynthesis, we also show that it can be applied to the study of primary metabolism. We illustrate this with examples from our work studying the members of the glycyl radical enzyme superfamily involved in choline and 4-hydroxyproline degradation in the human gut. Looking forward, we envision increased opportunities to use such information, with the combination of biochemical knowledge and computational tools poised to fuel a new revolution in our ability to connect genes and their biochemical functions. In particular, we note a need for methods that computationally formalize the functional association between genes when such associations are not obvious from manual gene annotations. Such tools will drastically augment the feasibility and scope of gene cluster analysis and accelerate the discovery of new microbial enzymes, metabolites, and metabolic processes.

Bacterial Receiver Prototype for Molecular Communication using Rhamnose Operon in a Microfluidic Environment

Bacterial populations are promising candidates for the development of the receiver and transmitter nanomachines for molecular communication (MC). A bacterial receiver is required to uptake the information molecules and produce the detectable molecules following a regulation mechanism. We have constructed a novel bacterial MC receiver using an inducible bacterial L-rhamnoseregulating operon. The proposed bacterial receiver produces green fluorescent protein (GFP) in response to the L-rhamnose information molecules following a quite fast regulation mechanism. To fabricate the receiver, the bacterial population has been transformed using a plasmid harboring L-rhamnose operon genes and gene expressing GFP in a microfluidic environment. We mathematically model the reception process of information molecules and characterize the model parameters by comparing the simulation results of the model in the employed microfluidic environment and the data obtained from the experimental setup. Based on the experimental results, the receiver is able to switch between different low and high concentrations. This work paves the way for the fabrication and modeling of any bacterial operon-based receiver with any proteins rather than GFP. Further, our experimental results indicate that the proposed bacterial receiver has a faster response to information molecules compared to the previous bacterial receiver based on the quorum sensing (QS) process.

A Computational Framework for Identifying Promoter Sequences in Nonmodel Organisms Using RNA-seq Data Sets

Engineering microorganisms into biological factories that convert renewable feedstocks into valuable materials is a major goal of synthetic biology; however, for many nonmodel organisms, we do not yet have the genetic tools, such as suites of strong promoters, necessary to effectively engineer them. In this work, we developed a computational framework that can leverage standard RNA-seq data sets to identify sets of constitutive, strongly expressed genes and predict strong promoter signals within their upstream regions. The framework was applied to a diverse collection of RNA-seq data measured for the methanotroph Methylotuvimicrobium buryatense 5GB1 and identified 25 genes that were constitutively, strongly expressed across 12 experimental conditions. For each gene, the framework predicted short (27-30 nucleotide) sequences as candidate promoters and derived -35 and -10 consensus promoter motifs (TTGACA and TATAAT, respectively) for strong expression in M. buryatense. This consensus closely matches the canonical E. coli sigma-70 motif and was found to be enriched in promoter regions of the genome. A subset of promoter predictions was experimentally validated in a XylE reporter assay, including the consensus promoter, which showed high expression. The pmoC, pqqA, and ssrA promoter predictions were additionally screened in an experiment that scrambled the -35 and -10 signal sequences, confirming that transcription initiation was disrupted when these specific regions of the predicted sequence were altered. These results indicate that the computational framework can make biologically meaningful promoter predictions and identify key pieces of regulatory systems that can serve as foundational tools for engineering diverse microorganisms for biomolecule production.

Analysis of the chromosomal clustering of Fusarium-responsive wheat genes uncovers new players in the defence against head blight disease

There is increasing evidence that some functionally related, co-expressed genes cluster within eukaryotic genomes. We present a novel pipeline that delineates such eukaryotic gene clusters. Using this tool for bread wheat, we uncovered 44 clusters of genes that are responsive to the fungal pathogen Fusarium graminearum. As expected, these Fusarium-responsive gene clusters (FRGCs) included metabolic gene clusters, many of which are associated with disease resistance, but hitherto not described for wheat. However, the majority of the FRGCs are non-metabolic, many of which contain clusters of paralogues, including those implicated in plant disease responses, such as glutathione transferases, MAP kinases, and germin-like proteins. 20 of the FRGCs encode nonhomologous, non-metabolic genes (including defence-related genes). One of these clusters includes the characterised Fusarium resistance orphan gene, TaFROG. Eight of the FRGCs map within 6 FHB resistance loci. One small QTL on chromosome 7D (4.7 Mb) encodes eight Fusarium-responsive genes, five of which are within a FRGC. This study provides a new tool to identify genomic regions enriched in genes responsive to specific traits of interest and applied herein it highlighted gene families, genetic loci and biological pathways of importance in the response of wheat to disease.

GCsnap: Interactive Snapshots for the Comparison of Protein-Coding Genomic Contexts

The biological function and evolutionary history of protein-coding genes are not only written in their nucleotide sequences. The comparison of genomic contexts throughout different lineages may highlight genomic mechanisms in the generation of new protein families, while the conservation of gene clusters may unravel, for instance, metabolic pathways. Various tools and databases exist that allow for the analysis and comparison of genomic contexts, but each has its own limitations. Online databases allow for quick comparisons, but only for those genomes for which data were pre-calculated. More advanced tools may allow for the comparison of any genome, but are often limited to a given phylogenetic kingdom or provide only a snapshot of the genomic contexts without further information about the genes involved. Here, we introduce GCsnap, a flexible Python-based tool that allows for the interactive comparison of the genomic contexts of protein-coding genes from any genome at any taxonomic level, integrating them with functional and structural information. By connecting the output to different protein databases, users can navigate through the different genomic contexts from a simple interactive platform, facilitating the further analysis of the contexts found. GCsnap is not limited to a single input format, can perform batch jobs and accepts protein classification maps. Results are stored in detailed, human and machine-readable files, and customizable, publication-ready figures. GCsnap is freely available from https://github.com/JoanaMPereira/GCsnap and can be set up easily on any computer.

Proximity proteomics in a marine diatom reveals a putative cell surface-to-chloroplast iron trafficking pathway

Iron is a biochemically critical metal cofactor in enzymes involved in photosynthesis, cellular respiration, nitrate assimilation, nitrogen fixation, and reactive oxygen species defense. Marine microeukaryotes have evolved a phytotransferrin-based iron uptake system to cope with iron scarcity, a major factor limiting primary productivity in the global ocean. Diatom phytotransferrin is endocytosed; however, proteins downstream of this environmentally ubiquitous iron receptor are unknown. We applied engineered ascorbate peroxidase APEX2-based subcellular proteomics to catalog proximal proteins of phytotransferrin in the model marine diatom Phaeodactylum tricornutum. Proteins encoded by poorly characterized iron-sensitive genes were identified including three that are expressed from a chromosomal gene cluster. Two of them showed unambiguous colocalization with phytotransferrin adjacent to the chloroplast. Further phylogenetic, domain, and biochemical analyses suggest their involvement in intracellular iron processing. Proximity proteomics holds enormous potential to glean new insights into iron acquisition pathways and beyond in these evolutionarily, ecologically, and biotechnologically important microalgae.

Molecular Mechanisms of Phosphate Sensing, Transport and Signalling in Streptomyces and Related Actinobacteria

Phosphorous, in the form of phosphate, is a key element in the nutrition of all living beings. In nature, it is present in the form of phosphate salts, organophosphates, and phosphonates. Bacteria transport inorganic phosphate by the high affinity phosphate transport system PstSCAB, and the low affinity PitH transporters. The PstSCAB system consists of four components. PstS is the phosphate binding protein and discriminates between arsenate and phosphate. In the Streptomyces species, the PstS protein, attached to the outer side of the cell membrane, is glycosylated and released as a soluble protein that lacks its phosphate binding ability. Transport of phosphate by the PstSCAB system is drastically regulated by the inorganic phosphate concentration and mediated by binding of phosphorylated PhoP to the promoter of the PstSCAB operon. In Mycobacterium smegmatis, an additional high affinity transport system, PhnCDE, is also under PhoP regulation. Additionally, Streptomyces have a duplicated low affinity phosphate transport system encoded by the pitH1–pitH2 genes. In this system phosphate is transported as a metal-phosphate complex in simport with protons. Expression of pitH2, but not that of pitH1 in Streptomyces coelicolor, is regulated by PhoP. Interestingly, in many Streptomyces species, three gene clusters pitH1–pstSCAB–ppk (for a polyphosphate kinase), are linked in a supercluster formed by nine genes related to phosphate metabolism. Glycerol-3-phosphate may be transported by the actinobacteria Corynebacterium glutamicum that contains a ugp gene cluster for glycerol-3-P uptake, but the ugp cluster is not present in Streptomyces genomes. Sugar phosphates and nucleotides are used as phosphate source by the Streptomyces species, but there is no evidence of the uhp gene involved in the transport of sugar phosphates. Sugar phosphates and nucleotides are dephosphorylated by extracellular phosphatases and nucleotidases. An isolated uhpT gene for a hexose phosphate antiporter is present in several pathogenic corynebacteria, such as Corynebacterium diphtheriae, but not in non-pathogenic ones. Phosphonates are molecules that contains phosphate linked covalently to a carbon atom through a very stable C–P bond. Their utilization requires the phnCDE genes for phosphonates/phosphate transport and genes for degradation, including those for the subunits of the C–P lyase. Strains of the Arthrobacter and Streptomyces genera were reported to degrade simple phosphonates, but bioinformatic analysis reveals that whole sets of genes for putative phosphonate degradation are present only in three Arthrobacter species and a few Streptomyces species. Genes encoding the C–P lyase subunits occur in several Streptomyces species associated with plant roots or with mangroves, but not in the laboratory model Streptomyces species; however, the phnCDE genes that encode phosphonates/phosphate transport systems are frequent in Streptomyces species, suggesting that these genes, in the absence of C–P lyase genes, might be used as surrogate phosphate transporters. In summary, Streptomyces and related actinobacteria seem to be less versatile in phosphate transport systems than Enterobacteria.

Protein–protein interaction network: an emerging tool for understanding fish disease in aquaculture

Protein–protein interactions (PPIs) play integral roles in a wide range of biological processes that regulate the overall growth, development, physiology and disease in living organisms. With the advancement of high‐throughput sequencing technologies, increasing numbers of PPI networks are being predicted and annotated, and these contribute greatly towards the understanding of pathogenesis and the discovery of novel drug targets for the treatment of diseases. The use of this tool is gaining popularity in the identification, understanding and treatment of diseases in humans and plants. Due to the importance of aquaculture in tackling the global food crisis by producing cheap and high‐quality protein source, the maintenance of the overall health status of aquaculture species is essential. With the increasing omics data on aquaculture species, the PPI network is an emerging tool for fish health maintenance. In this review, we first introduce the concept of PPI network, how they are discovered and their general application. Then, the current status of aquaculture and disease in aquaculture are discussed. The different applications of PPI network in aquaculture fish disease management such as biomarker identification, mechanism prediction, understanding of host–pathogen interaction, understanding of pathogen co‐infection interaction, and potential development of vaccines and treatments are subsequently highlighted. It is hoped that this emerging tool – PPI network – would deepen our understanding of the pathogenesis of various diseases and hasten the prevention and treatment processes in aquaculture species.

Endophytic Fungi: From Symbiosis to Secondary Metabolite Communications or Vice Versa?

Endophytic fungi (EF) are a group of fascinating host-associated fungal communities that colonize the intercellular or intracellular spaces of host tissues, providing beneficial effects to their hosts while gaining advantages. In recent decades, accumulated research on endophytic fungi has revealed their biodiversity, wide-ranging ecological distribution, and multidimensional interactions with host plants and other microbiomes in the symbiotic continuum. In this review, we highlight the role of secondary metabolites (SMs) as effectors in these multidimensional interactions, and the biosynthesis of SMs in symbiosis via complex gene expression regulation mechanisms in the symbiotic continuum and via the mimicry or alteration of phytochemical production in host plants. Alternative biological applications of SMs in modern medicine, agriculture, and industry and their major classes are also discussed. This review recapitulates an introduction to the research background, progress, and prospects of endophytic biology, and discusses problems and substantive challenges that need further study.

Additional Layer of Regulation via Convergent Gene Orientation in Yeasts

Convergent gene pairs can produce transcripts with complementary sequences. We had shown that mRNA duplexes form in vivo in Saccharomyces cerevisiae via interactions of mRNA overlapping 3′-ends and can lead to posttranscriptional regulatory events. Here we show that mRNA duplex formation is restricted to convergent genes separated by short intergenic distance, independently of their 3′-untranslated region (UTR) length. We disclose an enrichment in genes involved in biological processes related to stress among these convergent genes. They are markedly conserved in convergent orientation in budding yeasts, meaning that this mode of posttranscriptional regulation could be shared in these organisms, conferring an additional level for modulating stress response. We thus investigated the mechanistic advantages potentially conferred by 3′-UTR mRNA interactions. Analysis of genome-wide transcriptome data revealed that Pat1 and Lsm1 factors, having 3′-UTR binding preference and participating to the remodeling of messenger ribonucleoprotein particles, bind differently these messenger-interacting mRNAs forming duplexes in comparison to mRNAs that do not interact (solo mRNAs). Functionally, messenger-interacting mRNAs show limited translational repression upon stress. We thus propose that mRNA duplex formation modulates the regulation of mRNA expression by limiting their access to translational repressors. Our results thus show that posttranscriptional regulation is an additional factor that determines the order of coding genes.

Next-generation metabolic engineering approaches towards development of plant cell suspension cultures as specialized metabolite producing biofactories

Plant cell suspension culture (PCSC) has emerged as a viable technology to produce plant specialized metabolites (PSM). While Taxol® and ginsenoside are two examples of successfully commercialized PCSC-derived PSM, widespread utilization of the PCSC platform has yet to be realized primarily due to a lack of understanding of the molecular genetics of PSM biosynthesis. Recent advances in computational, molecular and synthetic biology tools provide the opportunity to rapidly characterize and harness the specialized metabolic potential of plants. Here, we discuss the prospects of integrating computational modeling, artificial intelligence, and precision genome editing (CRISPR/Cas and its variants) toolboxes to discover the genetic regulators of PSM. We also explore how synthetic biology can be applied to develop metabolically optimized PSM-producing native and heterologous PCSC systems. Taken together, this review provides an interdisciplinary approach to realize and link the potential of next-generation computational and molecular tools to convert PCSC into commercially viable PSM-producing biofactories.