A Bidirectional Non-Coding RNA Promoter Mediates Long-Range Gene Expression Regulation.

Recent evidence suggests that human gene promoters display gene expression regulatory mechanisms beyond the typical single gene local transcription modulation. In mammalian genomes, genes with an associated bidirectional promoter are abundant; bidirectional promoter architecture serves as a regulatory hub for a gene pair expression. However, it has been suggested that its contribution to transcriptional regulation might exceed local transcription initiation modulation. Despite their abundance, the functional consequences of bidirectional promoter architecture remain largely unexplored. This work studies the long-range gene expression regulatory role of a long non-coding RNA gene promoter using chromosome conformation capture methods. We found that this particular bidirectional promoter contributes to distal gene expression regulation in a target-specific manner by establishing promoter-promoter interactions. In particular, we validated that the promoter-promoter interactions of this regulatory element with the promoter of distal gene BBX contribute to modulating the transcription rate of this gene; removing the bidirectional promoter from its genomic context leads to a rearrangement of BBX promoter-enhancer interactions and to increased gene expression. Moreover, long-range regulatory functionality is not directly dependent on its associated non-coding gene pair expression levels.

Sequencing and description of the genome of a strain of Stenotrophomonas geniculata isolated from a patient infected with COVID-19 at Hospital Regional No.1 de Charo, Michoacán, México.

Stenotrophomonas is a bacterial genus that can be found in various environments, such as water, soil, and clinical samples. Due to their high genetic and phenotypic diversity, it is difficult to properly identify and classify all isolates. The COVID-19 pandemic caused an increase in nosocomial infections, which played a major role in the high mortality rate among patients in intensive care. This is the first report of the identification of S. geniculata as a nosocomial opportunistic pathogen isolated from a patient with COVID-19. Their genome was isolated, sequenced, and assembled, and it consists of 4,488,090 bp in 24 contigs, 4,103 coding sequences, and a G+C content of 66.58%.

Betaglycan promoter activity is differentially regulated during myogenesis in zebrafish embryo somites.

BACKGROUND: Betaglycan, also known as the TGFß type III receptor (Tgfbr3), is a co-receptor that modulates TGFß family signaling. Tgfbr3 is upregulated during C2C12 myoblast differentiation and expressed in mouse embryos myocytes. RESULTS: To investigate tgfbr3 transcriptional regulation during zebrafish embryonic myogenesis, we cloned a 3.2 kb promoter fragment that drives reporter transcription during C2C12 myoblasts differentiation and in the Tg(tgfbr3:mCherry) transgenic zebrafish. We detect tgfbr3 protein and mCherry expression in the adaxial cells concomitantly with the onset of their radial migration to become slow-twitch muscle fibers in the Tg(tgfbr3:mCherry). Remarkably, this expression displays a measurable antero-posterior somitic gradient expression. CONCLUSIONS: tgfbr3 is transcriptionally regulated during somitic muscle development in zebrafish with an antero-posterior gradient expression that preferentially marks the adaxial cells and their descendants.

Identifying similarities at metabolic pathways with a strategy of Enzymatic Step Sequences.

An easy and fast strategy to compare functionally the metabolic maps is described. The KEGG metabolic maps are transformed into linear Enzymatic Step Sequences (ESS) using the Breadth First Search (BFS) algorithm. To do this, the KGML files are retrieved, and directed graph representations are created; where the nodes represent enzymes or enzymatic complexes, and the edges represent a compound, that is the 'product' from one reaction and a 'substrate' for the next. Then, a set of initialization nodes are selected, and used as the root for the construction of the BFS tree. This tree is used as a guide to the construction of the ESS. From each leaf (terminal node), the path is traced backwards until it reaches the root metabolic map and with two or fewer neighbors in the graph. In a second step, the ESS are compared with a Dynamic Programing algorithm, considering an "ad hoc" substitution matrix, and minimizing the global score. The dissimilarity values between two EC numbers ranged from 0 to 1, where 0 indicates similar EC numbers, and 1 indicates different EC numbers. Finally, the alignment is evaluated by using the normalized entropy-based function, considering a threshold of ≤ 0.27 as significant.•The KEGG metabolic maps are transformed into linear Enzymatic Step Sequences (ESS) using the Breadth First Search (BFS) algorithm.•Nodes represent enzymes or enzymatic complexes, and the edges represent a compound, that is 'product' from one reaction and a 'substrate' for the next.•The ESS are compared with a Dynamic Programing algorithm, considering an "ad hoc" substitution matrix, and minimizing the global score.

Positively charged amino acids at the N terminus of select mitochondrial proteins mediate early recognition by import proteins αß'-NAC and Sam37.

A major challenge in eukaryotic cells is the proper distribution of nuclear-encoded proteins to the correct organelles. For a subset of mitochondrial proteins, a signal sequence at the N terminus (matrix-targeting sequence [MTS]) is recognized by protein complexes to ensure their proper translocation into the organelle. However, the early steps of mitochondrial protein targeting remain undeciphered. The cytosolic chaperone nascent polypeptide-associated complex (NAC), which in yeast is represented as the two different heterodimers αß-NAC and αß'-NAC, has been proposed to be involved during the early steps of mitochondrial protein targeting. We have previously described that the mitochondrial outer membrane protein Sam37 interacts with αß'-NAC and together promote the import of specific mitochondrial precursor proteins. In this work, we aimed to detect the region in the MTS of mitochondrial precursors relevant for their recognition by αß'-NAC during their sorting to the mitochondria. We used targeting signals of different mitochondrial proteins (αß'-NAC-dependent Oxa1 and αß'-NAC-independent Mdm38) and fused them to GFP to study their intracellular localization by biochemical and microscopy methods, and in addition followed their import kinetics in vivo. Our results reveal the presence of a positively charged amino acid cluster in the MTS of select mitochondrial precursors, such as Oxa1 and Fum1, which are crucial for their recognition by αß'-NAC. Furthermore, we explored the presence of this cluster at the N terminus of the mitochondrial proteome and propose a set of precursors whose proper localization depends on both αß'-NAC and Sam37.

Improved post-stroke spontaneous recovery by astrocytic extracellular vesicles.

Spontaneous recovery after a stroke accounts for a significant part of the neurological recovery in patients. However limited, the spontaneous recovery is mechanistically driven by axonal restorative processes for which several molecular cues have been previously described. We report the acceleration of spontaneous recovery in a preclinical model of ischemia/reperfusion in rats via a single intracerebroventricular administration of extracellular vesicles released from primary cortical astrocytes. We used magnetic resonance imaging and confocal and multiphoton microscopy to correlate the structural remodeling of the corpus callosum and striatocortical circuits with neurological performance during 21 days. We also evaluated the functionality of the corpus callosum by repetitive recordings of compound action potentials to show that the recovery facilitated by astrocytic extracellular vesicles was both anatomical and functional. Our data provide compelling evidence that astrocytes can hasten the basal recovery that naturally occurs post-stroke through the release of cellular mediators contained in extracellular vesicles.

Identification of functional signatures in the metabolism of the three cellular domains of life.

In order to identify common and specific enzymatic activities associated with the metabolism of the three cellular domains of life, the conservation and variations between the enzyme contents of Bacteria, Archaea, and Eukarya organisms were evaluated. To this end, the content of enzymes belonging to a particular pathway and their abundance and distribution in 1507 organisms that have been annotated and deposited in the KEGG database were assessed. In addition, we evaluated the consecutive enzymatic reaction pairs obtained from metabolic pathway reactions and transformed into sequences of enzymatic reactions, with catalytic activities encoded in the Enzyme Commission numbers, which are linked by a substrate. Both analyses are complementary: the first considers individual reactions associated with each organism and metabolic map, and the second evaluates the functional associations between pairs of consecutive reactions. From these comparisons, we found a set of five enzymatic reactions that were widely distributed in all the organisms and considered here as universal to Bacteria, Archaea, and Eukarya; whereas 132 pairs out of 3151 reactions were identified as significant, only 5 of them were found to be widely distributed in all the taxonomic divisions. However, these universal reactions are not widely distributed along the metabolic maps, suggesting their dispensability to all metabolic processes. Finally, we found that universal reactions are also associated with ancestral domains, such as those related to phosphorus-containing groups with a phosphate group as acceptor or those related to the ribulose-phosphate binding barrel, triosephosphate isomerase, and D-ribose-5-phosphate isomerase (RpiA) lid domain, among others. Therefore, we consider that this analysis provides clues about the functional constraints associated with the repertoire of enzymatic functions per organism.

Understanding the Mechanisms Behind the Response to Environmental Perturbation in Microbial Mats: A Metagenomic-Network Based Approach.

To date, it remains unclear how anthropogenic perturbations influence the dynamics of microbial communities, what general patterns arise in response to disturbance, and whether it is possible to predict them. Here, we suggest the use of microbial mats as a model of study to reveal patterns that can illuminate the ecological processes underlying microbial dynamics in response to stress. We traced the responses to anthropogenic perturbation caused by water depletion in microbial mats from Cuatro Cienegas Basin (CCB), Mexico, by using a time-series spatially resolved analysis in a novel combination of three computational approaches. First, we implemented MEBS (Multi-genomic Entropy-Based Score) to evaluate the dynamics of major biogeochemical cycles across spatio-temporal scales with a single informative value. Second, we used robust Time Series-Ecological Networks (TS-ENs) to evaluate the total percentage of interactions at different taxonomic levels. Lastly, we utilized network motifs to characterize specific interaction patterns. Our results indicate that microbial mats from CCB contain an enormous taxonomic diversity with at least 100 phyla, mainly represented by members of the rare biosphere (RB). Statistical ecological analyses point out a clear involvement of anaerobic guilds related to sulfur and methane cycles during wet versus dry conditions, where we find an increase in fungi, photosynthetic, and halotolerant taxa. TS-ENs indicate that in wet conditions, there was an equilibrium between cooperation and competition (positive and negative relationships, respectively), while under dry conditions there is an over-representation of negative relationships. Furthermore, most of the keystone taxa of the TS-ENs at family level are members of the RB and the microbial mat core highlighting their crucial role within the community. Our results indicate that microbial mats are more robust to perturbation due to redundant functions that are likely shared among community members in the highly connected TS-ENs with density values close to one (≈0.9). Finally, we provide evidence that suggests that a large taxonomic diversity where all community members interact with each other (low modularity), the presence of permanent of low-abundant taxa, and an increase in competition can be potential buffers against environmental disturbance in microbial mats.

MEBS, a software platform to evaluate large (meta)genomic collections according to their metabolic machinery: unraveling the sulfur cycle.

The increasing number of metagenomic and genomic sequences has dramatically improved our understanding of microbial diversity, yet our ability to infer metabolic capabilities in such datasets remains challenging. We describe the Multigenomic Entropy Based Score pipeline (MEBS), a software platform designed to evaluate, compare, and infer complex metabolic pathways in large "omic" datasets, including entire biogeochemical cycles. MEBS is open source and available through https://github.com/eead-csic-compbio/metagenome_Pfam_score. To demonstrate its use, we modeled the sulfur cycle by exhaustively curating the molecular and ecological elements involved (compounds, genes, metabolic pathways, and microbial taxa). This information was reduced to a collection of 112 characteristic Pfam protein domains and a list of complete-sequenced sulfur genomes. Using the mathematical framework of relative entropy (H΄), we quantitatively measured the enrichment of these domains among sulfur genomes. The entropy of each domain was used both to build up a final score that indicates whether a (meta)genomic sample contains the metabolic machinery of interest and to propose marker domains in metagenomic sequences such as DsrC (PF04358). MEBS was benchmarked with a dataset of 2107 non-redundant microbial genomes from RefSeq and 935 metagenomes from MG-RAST. Its performance, reproducibility, and robustness were evaluated using several approaches, including random sampling, linear regression models, receiver operator characteristic plots, and the area under the curve metric (AUC). Our results support the broad applicability of this algorithm to accurately classify (AUC = 0.985) hard-to-culture genomes (e.g., Candidatus Desulforudis audaxviator), previously characterized ones, and metagenomic environments such as hydrothermal vents, or deep-sea sediment. Our benchmark indicates that an entropy-based score can capture the metabolic machinery of interest and can be used to efficiently classify large genomic and metagenomic datasets, including uncultivated/unexplored taxa.

Identification of DNA Methyltransferase Genes in Human Pathogenic Bacteria by Comparative Genomics.

DNA methylation plays an important role in gene expression and virulence in some pathogenic bacteria. In this report, we describe DNA methyltransferases (MTases) present in human pathogenic bacteria and compared them with related species, which are not pathogenic or less pathogenic, based in comparative genomics. We performed a search in the KEGG database of the KEGG database orthology groups associated with adenine and cytosine DNA MTase activities (EC: 2.1.1.37, EC: 2.1.1.113 and EC: 2.1.1.72) in 37 human pathogenic species and 18 non/less pathogenic relatives and performed comparisons of the number of these MTases sequences according to their genome size, the DNA MTase type and with their non-less pathogenic relatives. We observed that Helicobacter pylori and Neisseria spp. presented the highest number of MTases while ten different species did not present a predicted DNA MTase. We also detected a significant increase of adenine MTases over cytosine MTases (2.19 vs. 1.06, respectively, p < 0.001). Adenine MTases were the only MTases associated with restriction modification systems and DNA MTases associated with type I restriction modification systems were more numerous than those associated with type III restriction modification systems (0.84 vs. 0.17, p < 0.001); additionally, there was no correlation with the genome size and the total number of DNA MTases, indicating that the number of DNA MTases is related to the particular evolution and lifestyle of specific species, regulating the expression of virulence genes in some pathogenic bacteria.

Correlation of Metabolic Variables with the Number of ORFs in Human Pathogenic and Phylogenetically Related Non- or Less-Pathogenic Bacteria.

To date, a few works have performed a correlation of metabolic variables in bacteria; however specific correlations with these variables have not been reported. In this work, we included 36 human pathogenic bacteria and 18 non- or less-pathogenic-related bacteria and obtained all metabolic variables, including enzymes, metabolic pathways, enzymatic steps and specific metabolic pathways, and enzymatic steps of particular metabolic processes, from a reliable metabolic database (KEGG). Then, we correlated the number of the open reading frames (ORF) with these variables and with the proportions of these variables, and we observed a negative correlation with the proportion of enzymes (r = -0.506, p < 0.0001), metabolic pathways (r = -0.871, p < 00.0001), enzymatic reactions (r = -0.749, p < 00.0001), and with the proportions of central metabolism variables as well as a positive correlation with the proportions of multistep reactions (r = 0.650, p < 00.0001) and secondary metabolism variables. The proportion of multifunctional reactions (r: -0.114, p = 0.41) and the proportion of enzymatic steps (r: -0.205, p = 0.14) did not present a significant correlation. These correlations indicate that as the size of a genome (measured in the number of ORFs) increases, the proportion of genes that encode enzymes significantly diminishes (especially those related to central metabolism), suggesting that when essential metabolic pathways are complete, an increase in the number of ORFs does not require a similar increase in the metabolic pathways and enzymes, but only a slight increase is sufficient to cope with a large genome.

The alignment of enzymatic steps reveals similar metabolic pathways and probable recruitment events in Gammaproteobacteria.

BACKGROUND: It is generally accepted that gene duplication followed by functional divergence is one of the main sources of metabolic diversity. In this regard, there is an increasing interest in the development of methods that allow the systematic identification of these evolutionary events in metabolism. Here, we used a method not based on biomolecular sequence analysis to compare and identify common and variable routes in the metabolism of 40 Gammaproteobacteria species. METHOD: The metabolic maps deposited in the KEGG database were transformed into linear Enzymatic Step Sequences (ESS) by using the breadth-first search algorithm. These ESS represent subsequent enzymes linked to each other, where their catalytic activities are encoded in the Enzyme Commission numbers. The ESS were compared in an all-against-all (pairwise comparisons) approach by using a dynamic programming algorithm, leaving only a set of significant pairs. RESULTS AND CONCLUSION: From these comparisons, we identified a set of functionally conserved enzymatic steps in different metabolic maps, in which cell wall components and fatty acid and lysine biosynthesis were included. In addition, we found that pathways associated with biosynthesis share a higher proportion of similar ESS than degradation pathways and secondary metabolism pathways. Also, maps associated with the metabolism of similar compounds contain a high proportion of similar ESS, such as those maps from nucleotide metabolism pathways, in particular the inosine monophosphate pathway. Furthermore, diverse ESS associated with the low part of the glycolysis pathway were identified as functionally similar to multiple metabolic pathways. In summary, our comparisons may help to identify similar reactions in different metabolic pathways and could reinforce the patchwork model in the evolution of metabolism in Gammaproteobacteria.

Increments and duplication events of enzymes and transcription factors influence metabolic and regulatory diversity in prokaryotes.

In this work, the content of enzymes and DNA-binding transcription factors (TFs) in 794 non-redundant prokaryotic genomes was evaluated. The identification of enzymes was based on annotations deposited in the KEGG database as well as in databases of functional domains (COG and PFAM) and structural domains (Superfamily). For identifications of the TFs, hidden Markov profiles were constructed based on well-known transcriptional regulatory families. From these analyses, we obtained diverse and interesting results, such as the negative rate of incremental changes in the number of detected enzymes with respect to the genome size. On the contrary, for TFs the rate incremented as the complexity of genome increased. This inverse related performance shapes the diversity of metabolic and regulatory networks and impacts the availability of enzymes and TFs. Furthermore, the intersection of the derivatives between enzymes and TFs was identified at 9,659 genes, after this point, the regulatory complexity grows faster than metabolic complexity. In addition, TFs have a low number of duplications, in contrast to the apparent high number of duplications associated with enzymes. Despite the greater number of duplicated enzymes versus TFs, the increment by which duplicates appear is higher in TFs. A lower proportion of enzymes among archaeal genomes (22%) than in the bacterial ones (27%) was also found. This low proportion might be compensated by the interconnection between the metabolic pathways in Archaea. A similar proportion was also found for the archaeal TFs, for which the formation of regulatory complexes has been proposed. Finally, an enrichment of multifunctional enzymes in Bacteria, as a mechanism of ecological adaptation, was detected.