pyPGCF: A Python Software for Phylogenomic Analysis, Species Demarcation, Identification of Core, and Fingerprint Proteins of Bacterial Genomes That Are Important for Plants.

This computational protocol describes how to use pyPGCF, a python software package that runs in the linux environment, in order to analyze bacterial genomes and perform: (i) phylogenomic analysis, (ii) species demarcation, (iii) identification of the core proteins of a bacterial genus and its individual species, (iv) identification of species-specific fingerprint proteins that are found in all strains of a species and, at the same time, are absent from all other species of the genus, (v) functional annotation of the core and fingerprint proteins with eggNOG, and (vi) identification of secondary metabolite biosynthetic gene clusters (smBGCs) with antiSMASH. This software has already been implemented to analyze bacterial genera and species that are important for plants (e.g., Pseudomonas, Bacillus, Streptomyces). In addition, we provide a test dataset and example commands showing how to analyze 165 genomes from 55 species of the genus Bacillus. The main advantages of pyPGCF are that: (i) it uses adjustable orthology cut-offs, (ii) it identifies species-specific fingerprints, and (iii) its computational cost scales linearly with the number of genomes being analyzed. Therefore, pyPGCF is able to deal with a very large number of bacterial genomes, in reasonable timescales, using widely available levels of computing power.

Synthetic yeast chromosome XI design provides a testbed for the study of extrachromosomal circular DNA dynamics.

We describe construction of the synthetic yeast chromosome XI (synXI) and reveal the effects of redesign at non-coding DNA elements. The 660-kb synthetic yeast genome project (Sc2.0) chromosome was assembled from synthesized DNA fragments before CRISPR-based methods were used in a process of bug discovery, redesign, and chromosome repair, including precise compaction of 200 kb of repeat sequence. Repaired defects were related to poor centromere function and mitochondrial health and were associated with modifications to non-coding regions. As part of the Sc2.0 design, loxPsym sequences for Cre-mediated recombination are inserted between most genes. Using the GAP1 locus from chromosome XI, we show that these sites can facilitate induced extrachromosomal circular DNA (eccDNA) formation, allowing direct study of the effects and propagation of these important molecules. Construction and characterization of synXI contributes to our understanding of non-coding DNA elements, provides a useful tool for eccDNA study, and will inform future synthetic genome design.

A panoramic view of the genomic landscape of the genus Streptomyces.

We delineate the evolutionary plasticity of the ecologically and biotechnologically important genus Streptomyces, by analysing the genomes of 213 species. Streptomycetes genomes demonstrate high levels of internal homology, whereas the genome of their last common ancestor was already complex. Importantly, we identify the species-specific fingerprint proteins that characterize each species. Even among closely related species, we observed high interspecies variability of chromosomal protein-coding genes, species-level core genes, accessory genes and fingerprints. Notably, secondary metabolite biosynthetic gene clusters (smBGCs), carbohydrate-active enzymes (CAZymes) and protein-coding genes bearing the rare TTA codon demonstrate high intraspecies and interspecies variability, which emphasizes the need for strain-specific genomic mining. Highly conserved genes, such as those specifying genus-level core proteins, tend to occur in the central region of the chromosome, whereas those encoding proteins with evolutionarily volatile species-level fingerprints, smBGCs, CAZymes and TTA-codon-bearing genes are often found towards the ends of the linear chromosome. Thus, the chromosomal arms emerge as the part of the genome that is mainly responsible for rapid adaptation at the species and strain level. Finally, we observed a moderate, but statistically significant, correlation between the total number of CAZymes and three categories of smBGCs (siderophores, e-Polylysin and type III lanthipeptides) that are related to competition among bacteria.

A Comparative Analysis of the Core Proteomes within and among the Bacillus subtilis and Bacillus cereus Evolutionary Groups Reveals the Patterns of Lineage- and Species-Specific Adaptations.

By integrating phylogenomic and comparative analyses of 1104 high-quality genome sequences, we identify the core proteins and the lineage-specific fingerprint proteins of the various evolutionary clusters (clades/groups/species) of the Bacillus genus. As fingerprints, we denote those core proteins of a certain lineage that are present only in that particular lineage and absent in any other Bacillus lineage. Thus, these lineage-specific fingerprints are expected to be involved in particular adaptations of that lineage. Intriguingly, with a few notable exceptions, the majority of the Bacillus species demonstrate a rather low number of species-specific fingerprints, with the majority of them being of unknown function. Therefore, species-specific adaptations are mostly attributed to highly unstable (in evolutionary terms) accessory proteomes and possibly to changes at the gene regulation level. A series of comparative analyses consistently demonstrated that the progenitor of the Cereus Clade underwent an extensive genomic expansion of chromosomal protein-coding genes. In addition, the majority (76-82%) of the B. subtilis proteins that are essential or play a significant role in sporulation have close homologs in most species of both the Subtilis and the Cereus Clades. Finally, the identification of lineage-specific fingerprints by this study may allow for the future development of highly specific vaccines, therapeutic molecules, or rapid and low-cost molecular tests for species identification.

Combination of Genome-Scale Models and Bioreactor Dynamics to Optimize the Production of Commodity Chemicals.

The current production of a number of commodity chemicals relies on the exploitation of fossil fuels and hence has an irreversible impact on the environment. Biotechnological processes offer an attractive alternative by enabling the manufacturing of chemicals by genetically modified microorganisms. However, this alternative approach poses some important technical challenges that must be tackled to make it competitive. On the one hand, the design of biotechnological processes is based on trial-and-error approaches, which are not only costly in terms of time and money, but also result in suboptimal designs. On the other hand, the manufacturing of chemicals by biological processes is almost exclusively carried out by batch or fed-batch cultures. Given that batch cultures are expensive and not easy to scale, technical means must be developed to make continuous cultures feasible and efficient. In order to address these challenges, we have developed a mathematical model able to integrate in a single model both the genome-scale metabolic model for the organism synthesizing the chemical of interest and the dynamics of the bioreactor in which the organism is cultured. Such a model is based on the use of Flexible Nets, a modeling formalism for dynamical systems. The integration of a microscopic (organism) and a macroscopic (bioreactor) model in a single net provides an overall view of the whole system and opens the door to global optimizations. As a case study, the production of citramalate with respect to the substrate consumed by E. coli is modeled, simulated and optimized in order to find the maximum productivity in a steady-state continuous culture. The predicted computational results were consistent with the wet lab experiments.

Comparative Analysis of SARS-CoV-2 Variants of Concern, Including Omicron, Highlights Their Common and Distinctive Amino Acid Substitution Patterns, Especially at the Spike ORF.

In order to gain a deeper understanding of the recently emerged and highly divergent Omicron variant of concern (VoC), a study of amino acid substitution (AAS) patterns was performed and compared with those of the other four successful variants of concern (Alpha, Beta, Gamma, Delta) and one closely related variant of interest (VoI-Lambda). The Spike ORF consistently emerges as an AAS hotspot in all six lineages, but in Omicron this enrichment is significantly higher. The progenitors of each of these VoC/VoI lineages underwent positive selection in the Spike ORF. However, once they were established, their Spike ORFs have been undergoing purifying selection, despite the application of global vaccination schemes from 2021 onwards. Our analyses reject the hypothesis that the heavily mutated receptor binding domain (RBD) of the Omicron Spike was introduced via recombination from another closely related Sarbecovirus. Thus, successive point mutations appear as the most parsimonious scenario. Intriguingly, in each of the six lineages, we observed a significant number of AAS wherein the new residue is not present at any homologous site among the other known Sarbecoviruses. Such AAS should be further investigated as potential adaptations to the human host. By studying the phylogenetic distribution of AAS shared between the six lineages, we observed that the Omicron (BA.1) lineage had the highest number (8/10) of recurrent mutations.

Fission stories: using PomBase to understand Schizosaccharomyces pombe biology.

PomBase (www.pombase.org), the model organism database (MOD) for the fission yeast Schizosaccharomyces pombe, supports research within and beyond the S. pombe community by integrating and presenting genetic, molecular, and cell biological knowledge into intuitive displays and comprehensive data collections. With new content, novel query capabilities, and biologist-friendly data summaries and visualization, PomBase also drives innovation in the MOD community.

The Remarkable Evolutionary Plasticity of Coronaviruses by Mutation and Recombination: Insights for the COVID-19 Pandemic and the Future Evolutionary Paths of SARS-CoV-2.

Coronaviruses (CoVs) constitute a large and diverse subfamily of positive-sense single-stranded RNA viruses. They are found in many mammals and birds and have great importance for the health of humans and farm animals. The current SARS-CoV-2 pandemic, as well as many previous epidemics in humans that were of zoonotic origin, highlights the importance of studying the evolution of the entire CoV subfamily in order to understand how novel strains emerge and which molecular processes affect their adaptation, transmissibility, host/tissue tropism, and patho non-homologous genicity. In this review, we focus on studies over the last two years that reveal the impact of point mutations, insertions/deletions, and intratypic/intertypic homologous and non-homologous recombination events on the evolution of CoVs. We discuss whether the next generations of CoV vaccines should be directed against other CoV proteins in addition to or instead of spike. Based on the observed patterns of molecular evolution for the entire subfamily, we discuss five scenarios for the future evolutionary path of SARS-CoV-2 and the COVID-19 pandemic. Finally, within this evolutionary context, we discuss the recently emerged Omicron (B.1.1.529) VoC.

The Neighborhood of the Spike Gene Is a Hotspot for Modular Intertypic Homologous and Nonhomologous Recombination in Coronavirus Genomes.

Coronaviruses (CoVs) have very large RNA viral genomes with a distinct genomic architecture of core and accessory open reading frames (ORFs). It is of utmost importance to understand their patterns and limits of homologous and nonhomologous recombination, because such events may affect the emergence of novel CoV strains, alter their host range, infection rate, tissue tropism pathogenicity, and their ability to escape vaccination programs. Intratypic recombination among closely related CoVs of the same subgenus has often been reported; however, the patterns and limits of genomic exchange between more distantly related CoV lineages (intertypic recombination) need further investigation. Here, we report computational/evolutionary analyses that clearly demonstrate a substantial ability for CoVs of different subgenera to recombine. Furthermore, we show that CoVs can obtain-through nonhomologous recombination-accessory ORFs from core ORFs, exchange accessory ORFs with different CoV genera, with other viruses (i.e., toroviruses, influenza C/D, reoviruses, rotaviruses, astroviruses) and even with hosts. Intriguingly, most of these radical events result from double crossovers surrounding the Spike ORF, thus highlighting both the instability and mobile nature of this genomic region. Although many such events have often occurred during the evolution of various CoVs, the genomic architecture of the relatively young SARS-CoV/SARS-CoV-2 lineage so far appears to be stable.

Yeast Double Transporter Gene Deletion Library for Identification of Xenobiotic Carriers in Low or High Throughput.

The routes of uptake and efflux should be considered when developing new drugs so that they can effectively address their intracellular targets. As a general rule, drugs appear to enter cells via protein carriers that normally carry nutrients or metabolites. A previously developed pipeline that searched for drug transporters using Saccharomyces cerevisiae mutants carrying single-gene deletions identified import routes for most compounds tested. However, due to the redundancy of transporter functions, we propose that this methodology can be improved by utilizing double mutant strains in both low- and high-throughput screens. We constructed a library of over 14,000 strains harboring double deletions of genes encoding 122 nonessential plasma membrane transporters and performed low- and high-throughput screens identifying possible drug import routes for 23 compounds. In addition, the high-throughput assay enabled the identification of putative efflux routes for 21 compounds. Focusing on azole antifungals, we were able to identify the involvement of the myo-inositol transporter, Itr1p, in the uptake of these molecules and to confirm the role of Pdr5p in their export. IMPORTANCE Our library of double transporter deletion strains is a powerful tool for rapid identification of potential drug import and export routes, which can aid in determining the chemical groups necessary for transport via specific carriers. This information may be translated into a better design of drugs for optimal absorption by target tissues and the development of drugs whose utility is less likely to be compromised by the selection of resistant mutants.

A unifying modelling formalism for the integration of stoichiometric and kinetic models.

Current research on systems and synthetic biology relies heavily on mathematical models of the systems under study. The usefulness of such models depends on the quantity and quality of biological data, and on the availability of appropriate modelling formalisms that can gather and accommodate such data so that they can be exploited properly. Given our incomplete knowledge of biological systems and the fact that they consist of many subsystems, biological data are usually uncertain and heterogeneous. These facts hinder the use of mathematical models and computational methods. In the scope of dynamic biological systems, e.g. metabolic networks, this difficulty can be overcome by the novel modelling formalism of flexible nets (FNs). We show that an FN can combine, in a natural way, a stoichiometric model and a kinetic model. Moreover, the resulting net admits nonlinear dynamics and can be analysed in both transient and steady states.

Yeast Systems Biology: The Continuing Challenge of Eukaryotic Complexity.

Research on yeast has produced a plethora of tools and resources that have been central to the progress of systems biology. This chapter reviews these resources, explains the innovations that have been made since the first edition of this book, and introduces the constituent chapters of the current edition. The value of these resources not only in building and testing models of the functional networks of the yeast cell, but also in providing a foundation for network studies on the molecular basis of complex human diseases is considered. The gaps in this vast compendium of data, including enzyme kinetic characteristics, biomass composition, transport processes, and cell-cell interactions are discussed, as are the interactions between yeast cells and those of other species. The relevance of these studies to both traditional and advanced biotechnologies and to human medicine is considered, and the opportunities and challenges in using unicellular yeasts to model the systems of multicellular organisms are presented.

Mapping the Saccharomyces cerevisiae Spatial Proteome with High Resolution Using hyperLOPIT.

The subcellular localization of proteins is a posttranslational modification of paramount importance. The ability to study subcellular and organelle proteomes improves our understanding of cellular homeostasis and cellular dynamics. In this chapter, we describe a protocol for the unbiased and high-throughput study of protein subcellular localization in the yeast Saccharomyces cerevisiae: hyperplexed localization of organelle proteins by isotope tagging (hyperLOPIT), which involves biochemical fractionation of Saccharomyces cerevisiae and high resolution mass spectrometry-based protein quantitation using TMT 10-plex isobaric tags. This protocol enables the determination of the subcellular localizations of thousands of proteins in parallel in a single experiment and thereby deep sampling and high-resolution mapping of the spatial proteome.

Low complexity regions in the proteins of prokaryotes perform important functional roles and are highly conserved.

We provide the first high-throughput analysis of the properties and functional role of Low Complexity Regions (LCRs) in more than 1500 prokaryotic and phage proteomes. We observe that, contrary to a widespread belief based on older and sparse data, LCRs actually have a significant, persistent and highly conserved presence and role in many and diverse prokaryotes. Their specific amino acid content is linked to proteins with certain molecular functions, such as the binding of RNA, DNA, metal-ions and polysaccharides. In addition, LCRs have been repeatedly identified in very ancient, and usually highly expressed proteins of the translation machinery. At last, based on the amino acid content enriched in certain categories, we have developed a neural network web server to identify LCRs and accurately predict whether they can bind nucleic acids, metal-ions or are involved in chaperone functions. An evaluation of the tool showed that it is highly accurate for eukaryotic proteins as well.

Metabolic response to Parkinson's disease recapitulated by the haploinsufficient diploid yeast cells hemizygous for the adrenodoxin reductase gene.

Adrenodoxin reductase, a widely conserved mitochondrial P450 protein, catalyses essential steps in steroid hormone biosynthesis and is highly expressed in the adrenal cortex. The yeast adrenodoxin reductase homolog, Arh1p, is involved in cytoplasmic and mitochondrial iron homeostasis and is required for activity of enzymes containing an Fe-S cluster. In this paper, we investigated the response of yeast to the loss of a single copy of ARH1, an oxidoreductase of the mitochondrial inner membrane, which is among the few mitochondrial proteins that is essential for viability in yeast. The phenotypic, transcriptional, proteomic, and metabolic landscape indicated that Saccharomyces cerevisiae successfully adapted to this loss, displaying an apparently dosage-insensitive cellular response. However, a considered investigation of transcriptional regulation in ARH1-impaired yeast highlighted that a significant hierarchical reorganisation occurred, involving the iron assimilation and tyrosine biosynthetic processes. The interconnected roles of the iron and tyrosine pathways, coupled with oxidative processes, are of interest beyond yeast since they are involved in dopaminergic neurodegeneration associated with Parkinson's disease. The identification of similar responses in yeast, albeit preliminary, suggests that this simple eukaryote could have potential as a model system for investigating the regulatory mechanisms leading to the initiation and progression of early disease responses in humans.

Metaheuristic approaches in biopharmaceutical process development data analysis.

There is a growing interest in mining and handling of big data, which has been rapidly accumulating in the repositories of bioprocess industries. Biopharmaceutical industries are no exception; the implementation of advanced process control strategies based on multivariate monitoring techniques in biopharmaceutical production gave rise to the generation of large amounts of data. Real-time measurements of critical quality and performance attributes collected during production can be highly useful to understand and model biopharmaceutical processes. Data mining can facilitate the extraction of meaningful relationships pertaining to these bioprocesses, and predict the performance of future cultures. This review evaluates the suitability of various metaheuristic methods available for data pre-processing, which would involve the handling of missing data, the visualisation of the data, and dimension reduction; and for data processing, which would focus on modelling of the data and the optimisation of these models in the context of biopharmaceutical process development. The advantages and the associated challenges of employing different methodologies in pre-processing and processing of the data are discussed. In light of these evaluations, a summary guideline is proposed for handling and analysis of the data generated in biopharmaceutical process development.

High-energy guanine nucleotides as a signal capable of linking growth to cellular energy status via the control of gene transcription.

This mini-review considers the idea that guanylate nucleotide energy charge acts as an integrative signal for the regulation of gene expression in eukaryotic cells and discusses possible routes for that signal's transduction. Gene expression is intimately linked with cell nutrition and diverse signaling systems serve to coordinate the synthesis of proteins required for growth and proliferation with the prevailing cellular nutritional status. Using short pathways for the inducible and futile consumption of ATP or GTP in engineered cells of Saccharomyces cerevisiae, we have recently shown that GTP levels can also play a role in determining how genes act to respond to changes in cellular energy supply. This review aims to interpret the importance of GTP as an integrative signal in the context of an increasing body of evidence indicating the spatio-temporal complexity of cellular de novo purine nucleotide biosynthesis.

Hidden in plain sight: what remains to be discovered in the eukaryotic proteome?

The first decade of genome sequencing stimulated an explosion in the characterization of unknown proteins. More recently, the pace of functional discovery has slowed, leaving around 20% of the proteins even in well-studied model organisms without informative descriptions of their biological roles. Remarkably, many uncharacterized proteins are conserved from yeasts to human, suggesting that they contribute to fundamental biological processes (BP). To fully understand biological systems in health and disease, we need to account for every part of the system. Unstudied proteins thus represent a collective blind spot that limits the progress of both basic and applied biosciences. We use a simple yet powerful metric based on Gene Ontology BP terms to define characterized and uncharacterized proteins for human, budding yeast and fission yeast. We then identify a set of conserved but unstudied proteins in S. pombe, and classify them based on a combination of orthogonal attributes determined by large-scale experimental and comparative methods. Finally, we explore possible reasons why these proteins remain neglected, and propose courses of action to raise their profile and thereby reap the benefits of completing the catalogue of proteins' biological roles.