Lipid turnover through lipophagy in the newly identified extremophilic green microalga Chlamydomonas urium.

Autophagy is a central degradative pathway highly conserved among eukaryotes, including microalgae, which remains unexplored in extremophilic organisms. In this study, we described and characterized autophagy in the newly identified extremophilic green microalga Chlamydomonas urium, which was isolated from an acidic environment. The nuclear genome of C. urium was sequenced, assembled and annotated in order to identify autophagy-related genes. Transmission electron microscopy, immunoblotting, metabolomic and photosynthetic analyses were performed to investigate autophagy in this extremophilic microalga. The analysis of the C. urium genome revealed the conservation of core autophagy-related genes. We investigated the role of autophagy in C. urium by blocking autophagic flux with the vacuolar ATPase inhibitor concanamycin A. Our results indicated that inhibition of autophagic flux in this microalga resulted in a pronounced accumulation of triacylglycerols and lipid droplets (LDs). Metabolomic and photosynthetic analyses indicated that C. urium cells with impaired vacuolar function maintained an active metabolism. Such effects were not observed in the neutrophilic microalga Chlamydomonas reinhardtii. Inhibition of autophagic flux in C. urium uncovered an active recycling of LDs through lipophagy, a selective autophagy pathway for lipid turnover. This study provided the metabolic basis by which extremophilic algae are able to catabolize lipids in the vacuole.

ASACO: Automatic and Serial Analysis of CO-expression to discover gene modifiers with potential use in drug repurposing.

Massive gene expression analyses are widely used to find differentially expressed genes under specific conditions. The results of these experiments are often available in public databases that are undergoing a growth similar to that of molecular sequence databases in the past. This now allows novel secondary computational tools to emerge that use such information to gain new knowledge. If several genes have a similar expression profile across heterogeneous transcriptomics experiments, they could be functionally related. These associations are usually useful for the annotation of uncharacterized genes. In addition, the search for genes with opposite expression profiles is useful for finding negative regulators and proposing inhibitory compounds in drug repurposing projects. Here we present a new web application, Automatic and Serial Analysis of CO-expression (ASACO), which has the potential to discover positive and negative correlator genes to a given query gene, based on thousands of public transcriptomics experiments. In addition, examples of use are presented, comparing with previous contrasted knowledge. The results obtained propose ASACO as a useful tool to improve knowledge about genes associated with human diseases and noncoding genes. ASACO is available at http://www.bioinfocabd.upo.es/asaco/.

The most exposed regions of SARS-CoV-2 structural proteins are subject to strong positive selection and gene overlap may locally modify this behavior.

The SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic that emerged in 2019 has been an unprecedented event in international science, as it has been possible to sequence millions of genomes, tracking their evolution very closely. This has enabled various types of secondary analyses of these genomes, including the measurement of their sequence selection pressure. In this work, we have been able to measure the selective pressure of all the described SARS-CoV-2 genes, even analyzed by sequence regions, and we show how this type of analysis allows us to separate the genes between those subject to positive selection (usually those that code for surface proteins or those exposed to the host immune system) and those subject to negative selection because they require greater conservation of their structure and function. We have also seen that when another gene with an overlapping reading frame appears within a gene sequence, the overlapping sequence between the two genes evolves under a stronger purifying selection than the average of the non-overlapping regions of the main gene. We propose this type of analysis as a useful tool for locating and analyzing all the genes of a viral genome when an adequate number of sequences are available.IMPORTANCEWe have analyzed the selection pressure of all severe acute respiratory syndrome coronavirus 2 genes by means of the nonsynonymous (Ka) to synonymous (Ks) substitution rate. We found that protein-coding genes are exposed to strong positive selection, especially in the regions of interaction with other molecules (host receptor and genome of the virus itself). However, overlapping coding regions are more protected and show negative selection. This suggests that this measure could be used to study viral gene function as well as overlapping genes.

Analysis of bacterial pangenomes reduces CRISPR dark matter and reveals strong association between membranome and CRISPR-Cas systems.

CRISPR-Cas systems are prokaryotic acquired immunity mechanisms, which are found in 40% of bacterial genomes. They prevent viral infections through small DNA fragments called spacers. However, the vast majority of these spacers have not yet been associated with the virus they recognize, and it has been named CRISPR dark matter. By analyzing the spacers of tens of thousands of genomes from six bacterial species, we have been able to reduce the CRISPR dark matter from 80% to as low as 15% in some of the species. In addition, we have observed that, when a genome presents CRISPR-Cas systems, this is accompanied by particular sets of membrane proteins. Our results suggest that when bacteria present membrane proteins that make it compete better in its environment and these proteins are, in turn, receptors for specific phages, they would be forced to acquire CRISPR-Cas.

Influence of Agaricus bisporus establishment and fungicidal treatments on casing soil metataxonomy during mushroom cultivation.

The cultivation of edible mushroom is an emerging sector with a potential yet to be discovered. Unlike plants, it is a less developed agriculture where many studies are lacking to optimize the cultivation. In this work we have employed high-throughput techniques by next generation sequencing to screen the microbial structure of casing soil employed in mushroom cultivation (Agaricus bisporus) while sequencing V3-V4 of the 16S rRNA gene for bacteria and the ITS2 region of rRNA for. In addition, the microbiota dynamics and evolution (bacterial and fungal communities) in peat-based casing along the process of incubation of A. bisporus have been studied, while comparing the effect of fungicide treatment (chlorothalonil and metrafenone). Statistically significant changes in populations of bacteria and fungi were observed. Microbial composition differed significantly based on incubation day, changing radically from the original communities in the raw material to a specific microbial composition driven by the A. bisporus mycelium growth. Chlorothalonil treatment seems to delay casing colonization by A. bisporus. Proteobacteria and Bacteroidota appeared as the most dominant bacterial phyla. We observed a great change in the structure of the bacteria populations between day 0 and the following days. Fungi populations changed more gradually, with A. bisporus displacing the rest of the species as the cultivation cycle progresses. A better understanding of the microbial communities in the casing will hopefully allow us to increase the biological efficiency of the crop.

Genome editing in animals with minimal PAM CRISPR-Cas9 enzymes.

The requirement for Cas nucleases to recognize a specific PAM is a major restriction for genome editing. SpCas9 variants SpG and SpRY, recognizing NGN and NRN PAMs, respectively, have contributed to increase the number of editable genomic sites in cell cultures and plants. However, their use has not been demonstrated in animals. Here we study the nuclease activity of SpG and SpRY by targeting 40 sites in zebrafish and C. elegans. Delivered as mRNA-gRNA or ribonucleoprotein (RNP) complexes, SpG and SpRY were able to induce mutations in vivo, albeit at a lower rate than SpCas9 in equivalent formulations. This lower activity was overcome by optimizing mRNA-gRNA or RNP concentration, leading to mutagenesis at regions inaccessible to SpCas9. We also found that the CRISPRscan algorithm could help to predict SpG and SpRY targets with high activity in vivo. Finally, we applied SpG and SpRY to generate knock-ins by homology-directed repair. Altogether, our results expand the CRISPR-Cas targeting genomic landscape in animals.

Assessment of selection pressure exerted on genes from complete pangenomes helps to improve the accuracy in the prediction of new genes.

Bacterial genomes are massively sequenced, and they provide valuable data to better know the complete set of genes of a species. The analysis of thousands of bacterial strains can identify both shared genes and those appearing only in the pathogenic ones. Current computational gene finders facilitate this task but often miss some existing genes. However, the present availability of different genomes from the same species is useful to estimate the selective pressure applied on genes of complete pangenomes. It may assist in evaluating gene predictions either by checking the certainty of a new gene or annotating it as a gene under positive selection. Here, we estimated the selective pressure of 19 271 genes that are part of the pangenome of the human opportunistic pathogen Acinetobacter baumannii and found that most genes in this bacterium are subject to negative selection. However, 23% of them showed values compatible with positive selection. These latter were mainly uncharacterized proteins or genes required to evade the host defence system including genes related to resistance and virulence whose changes may be favoured to acquire new functions. Finally, we evaluated the utility of measuring selection pressure in the detection of sequencing errors and the validation of gene prediction.

E-learning strategies from a bioinformatics postgraduate programme to improve student engagement and completion rate.

Motivation: E-learning is the standard solution adopted in transnational study programmes for which multiple face-to-face learning places are not an option. Bioinformatics is compatible with e-learning because its resource requirements are low. Online learning, however, is usually associated with high dropout rates because students start from a very low computational level and/or they need support to conduct practical analyses on their own. Results: In this article, we analyse the academic results of an online bioinformatics educational programme based on learning communities. The programme has been offered by the Spanish Pablo de Olavide University for more than 5 years with a completion rate of close to 90%. Learning bioinformatics requires technical and operational competencies that can only be acquired through a practical methodology. We have thus developed a student-centred and problem-based constructivist learning model; the model uses faculty and peer mentoring to drive individual work and retain students. Regarding our innovative learning model, the recruitment level (i.e. the number of applicants per available places and international origin), the results obtained (i.e. the retention index and learning outcomes) as well as the satisfaction index expressed by students and faculty lead us to regard this programme as a successful strategy for online graduate learning in bioinformatics. Availability and implementation: All data and results for this article are available in the figures and supplementary files. The current syllabus (Supplementary File S7) and other details of the course are available at: https://www.upo.es/postgrado/Diploma-de-Especializacion-Analisis-Bioinformatico and https://www.upo.es/postgrado/Master-Analisis-Bioinformatico-Avanzado. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

L-Arginine Ameliorates Defective Autophagy in GM2 Gangliosidoses by mTOR Modulation.

AIMS: Tay-Sachs and Sandhoff diseases (GM2 gangliosidosis) are autosomal recessive disorders of lysosomal function that cause progressive neurodegeneration in infants and young children. Impaired hydrolysis catalysed by ß-hexosaminidase A (HexA) leads to the accumulation of GM2 ganglioside in neuronal lysosomes. Despite the storage phenotype, the role of autophagy and its regulation by mTOR has yet to be explored in the neuropathogenesis. Accordingly, we investigated the effects on autophagy and lysosomal integrity using skin fibroblasts obtained from patients with Tay-Sachs and Sandhoff diseases. RESULTS: Pathological autophagosomes with impaired autophagic flux, an abnormality confirmed by electron microscopy and biochemical studies revealing the accelerated release of mature cathepsins and HexA into the cytosol, indicating increased lysosomal permeability. GM2 fibroblasts showed diminished mTOR signalling with reduced basal mTOR activity. Accordingly, provision of a positive nutrient signal by L-arginine supplementation partially restored mTOR activity and ameliorated the cytopathological abnormalities. INNOVATION: Our data provide a novel molecular mechanism underlying GM2 gangliosidosis. Impaired autophagy caused by insufficient lysosomal function might represent a new therapeutic target for these diseases. CONCLUSIONS: We contend that the expression of autophagy/lysosome/mTOR-associated molecules may prove useful peripheral biomarkers for facile monitoring of treatment of GM2 gangliosidosis and neurodegenerative disorders that affect the lysosomal function and disrupt autophagy.

Protein-Coding Genes of Helicobacter pylori Predominantly Present Purifying Selection though Many Membrane Proteins Suffer from Selection Pressure: A Proposal to Analyze Bacterial Pangenomes.

The current availability of complete genome sequences has allowed knowing that bacterial genomes can bear genes not present in the genome of all the strains from a specific species. So, the genes shared by all the strains comprise the core of the species, but the pangenome can be much greater and usually includes genes appearing in one only strain. Once the pangenome of a species is estimated, other studies can be undertaken to generate new knowledge, such as the study of the evolutionary selection for protein-coding genes. Most of the genes of a pangenome are expected to be subject to purifying selection that assures the conservation of function, especially those in the core group. However, some genes can be subject to selection pressure, such as genes involved in virulence that need to escape to the host immune system, which is more common in the accessory group of the pangenome. We analyzed 180 strains of Helicobacter pylori, a bacterium that colonizes the gastric mucosa of half the world population and presents a low number of genes (around 1500 in a strain and 3000 in the pangenome). After the estimation of the pangenome, the evolutionary selection for each gene has been calculated, and we found that 85% of them are subject to purifying selection and the remaining genes present some grade of selection pressure. As expected, the latter group is enriched with genes encoding for membrane proteins putatively involved in interaction to host tissues. In addition, this group also presents a high number of uncharacterized genes and genes encoding for putative spurious proteins. It suggests that they could be false positives from the gene finders used for identifying them. All these results propose that this kind of analyses can be useful to validate gene predictions and functionally characterize proteins in complete genomes.

Inhibition of the NLRP3 inflammasome prevents ovarian aging.

Inflammation is a hallmark of aging and is negatively affecting female fertility. In this study, we evaluate the role of the NLRP3 inflammasome in ovarian aging and female fertility. Age-dependent increased expression of NLRP3 in the ovary was observed in WT mice during reproductive aging. High expression of NLRP3, caspase-1, and IL-1ß was also observed in granulosa cells from patients with ovarian insufficiency. Ablation of NLRP3 improved the survival and pregnancy rates and increased anti-Müllerian hormone levels and autophagy rates in ovaries. Deficiency of NLRP3 also reduced serum FSH and estradiol levels. Consistent with these results, pharmacological inhibition of NLRP3 using a direct NLRP3 inhibitor, MCC950, improved fertility in female mice to levels comparable to those of Nlrp3-/- mice. These results suggest that the NLRP3 inflammasome is implicated in the age-dependent loss of female fertility and position this inflammasome as a potential new therapeutic target for the treatment of infertility.

Serial co-expression analysis of host factors from SARS-CoV viruses highly converges with former high-throughput screenings and proposes key regulators.

The current genomics era is bringing an unprecedented growth in the amount of gene expression data, only comparable to the exponential growth of sequences in databases during the last decades. This data allow the design of secondary analyses that take advantage of this information to create new knowledge. One of these feasible analyses is the evaluation of the expression level for a gene through a series of different conditions or cell types. Based on this idea, we have developed Automatic and Serial Analysis of CO-expression, which performs expression profiles for a given gene along hundreds of heterogeneous and normalized transcriptomics experiments and discover other genes that show either a similar or an inverse behavior. It might help to discover co-regulated genes, and common transcriptional regulators in any biological model. The present severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is an opportunity to test this novel approach due to the wealth of data that are being generated, which could be used for validating results. Thus, we have identified 35 host factors in the literature putatively involved in the infectious cycle of SARS-CoV viruses and searched for genes tightly co-expressed with them. We have found 1899 co-expressed genes whose assigned functions are strongly related to viral cycles. Moreover, this set of genes heavily overlaps with those identified by former laboratory high-throughput screenings (with P-value near 0). Our results reveal a series of common regulators, involved in immune and inflammatory responses that might be key virus targets to induce the coordinated expression of SARS-CoV-2 host factors.

Isolation and genomic characterization of the ibuprofen-degrading bacterium Sphingomonas strain MPO218.

The presence of pharmaceutical compounds in waters and soils is of particular concern because these compounds can be biologically active, even at environmental concentrations. Most pharmaceutical contaminants result from inefficient removal of these compounds during wastewater treatment. Although microorganisms able to biodegrade pharmaceuticals compounds have been described, the isolation and characterization of new bacterial strains capable of degrading drugs remain important to improve the removal of this pollutant. In this work, we describe the Sphingomonas wittichii strain MPO218 as able to use ibuprofen as the sole carbon and energy source. The genome of MPO218 consists of a circular chromosome and two circular plasmids. Our analysis shows that the largest plasmid, named pIBU218, is conjugative and can horizontally transfer the capability of growing on ibuprofen after conjugation with another related bacterium, Sphingopyxis granuli TFA. This plasmid appears to be unstable since it undergoes different deletions in absence of selection when growth on ibuprofen is not selected. This is the first described example of a natural and conjugative plasmid that enables growth on ibuprofen and is another example of how horizontal gene transfer plays a crucial role in the evolution of bacteria.

Virulence role of the outer membrane protein CarO in carbapenem-resistant Acinetobacter baumannii.

Novel approaches to treat carbapenem-resistant Acinetobacter baumannii (CRAB) infections are urgently needed and anti-virulence drugs represent promising alternatives, but our knowledge on potential targets is scarce. We searched for potential A. baumannii virulence factors by whole-genome sequencing-based comparisons of CRAB clinical isolates causing bloodstream infections secondary to ventilator-associated pneumonia from demographics and clinically homogeneous patients, who received optimal treatment but with different clinical outcomes. Thus, the carO gene was interrupted in CRAB isolates from surviving patients, while it was intact in isolates from non-surviving patients, and proteomic/immunoblot techniques corroborated it. When the virulence role of A. baumannii CarO was analyzed in model systems, isogenic ΔcarO mutants and a CRAB clinical isolate with truncated CarO, showed lower ability to adhere and invade A549 cells and in vivo virulence. This unnoticed virulence role for CarO postulate this A. baumannii outer membrane protein as a potential target for new therapies against CRAB infections.

CRISPR sequences are sometimes erroneously translated and can contaminate public databases with spurious proteins containing spaced repeats.

The genomics era is resulting in the generation of a plethora of biological sequences that are usually stored in public databases. There are many computational tools that facilitate the annotation of these sequences, but sometimes they produce mistakes that enter the databases and can be propagated when erroneous data are used for secondary analyses, such as gene prediction or homology searching. While developing a computational gene finder based on protein-coding sequences, we discovered that the reference UniProtKB protein database is contaminated with some spurious sequences translated from DNA containing clustered regularly interspaced short palindromic repeats. We therefore encourage developers of prokaryotic computational gene finders and protein database curators to consider this source of error.

Ancient evolutionary signals of protein-coding sequences allow the discovery of new genes in the Drosophila melanogaster genome.

BACKGROUND: The current growth in DNA sequencing techniques makes of genome annotation a crucial task in the genomic era. Traditional gene finders focus on protein-coding sequences, but they are far from being exhaustive. The number of this kind of genes continuously increases due to new experimental data and development of improved bioinformatics algorithms. RESULTS: In this context, AnABlast represents a novel in silico strategy, based on the accumulation of short evolutionary signals identified by protein sequence alignments of low score. This strategy potentially highlights protein-coding regions in genomic sequences regardless of traditional homology or translation signatures. Here, we analyze the evolutionary information that the accumulation of these short signals encloses. Using the Drosophila melanogaster genome, we stablish optimal parameters for the accurate gene prediction with AnABlast and show that this new strategy significantly contributes to add genes, exons and pseudogenes regions, yet to be discovered in both already annotated and new genomes. CONCLUSIONS: AnABlast can be freely used to analyze genomic regions of whole genomes where it contributes to complete the previous annotation.

Serial co-expression analysis of host factors from SARS-CoV viruses highly converges with former high-throughput screenings and proposes key regulators and co-option of cellular pathways.

The current genomics era is bringing an unprecedented growth in the amount of gene expression data, only comparable to the exponential growth of sequences in databases during the last decades. This data now allows the design of secondary analyses that take advantage of this information to create new knowledge through specific computational approaches. One of these feasible analyses is the evaluation of the expression level for a gene through a series of different conditions or cell types. Based on this idea, we have developed ASACO, Automatic and Serial Analysis of CO-expression, which performs expression profiles for a given gene along hundreds of normalized and heterogeneous transcriptomics experiments and discover other genes that show either a similar or an inverse behavior. It might help to discover co-regulated genes, and even common transcriptional regulators in any biological model, including human diseases or microbial infections. The present SARS-CoV-2 pandemic is an opportunity to test this novel approach due to the wealth of data that is being generated, which could be used for validating results. In addition, new cell mechanisms identified could become new therapeutic targets. Thus, we have identified 35 host factors in the literature putatively involved in the infectious cycle of SARS-CoV and/or SARS-CoV-2 and searched for genes tightly co-expressed with them. We have found around 1900 co-expressed genes whose assigned functions are strongly related to viral cycles. Moreover, this set of genes heavily overlap with those identified by former laboratory high-throughput screenings (with p-value near 0). Some of these genes aim to cellular structures such as the stress granules, which could be essential for the virus replication and thereby could constitute potential targets in the current fight against the virus. Additionally, our results reveal a series of common transcription regulators, involved in immune and inflammatory responses, that might be key virus targets to induce the coordinated expression of SARS-CoV-2 host factors. All of this proves that ASACO can discover gene co-regulation networks with potential for proposing new genes, pathways and regulators participating in particular biological systems. Highlights: ASACO identifies regulatory associations of genes using public transcriptomics data.ASACO highlights new cell functions likely involved in the infection of coronavirus.Comparison with high-throughput screenings validates candidates proposed by ASACO.Genes co-expressed with host's genes used by SARS-CoV-2 are related to stress granules.

NLRP3 Inflammasome Inhibition by MCC950 in Aged Mice Improves Health via Enhanced Autophagy and PPARα Activity.

The NLRP3 inflammasome has emerged as an important regulator of metabolic disorders and age-related diseases in NLRP3-deficient mice. In this article, we determine whether, in old mice C57BL6J, the NLRP3 inflammasome inhibitor MCC950 is able to attenuate age-related metabolic syndrome to providing health benefits. We report that MCC950 attenuates metabolic and hepatic dysfunction in aged mice. In addition, MCC950 inhibited the Pi3K/AKT/mTOR pathway, enhanced autophagy, and activated peroxisome proliferator-activated receptor-α in vivo and in vitro. The data suggest that MCC950 mediates the protective effects by the mammalian target of rapamycin inhibition, thus activating autophagy and peroxisome proliferator-activated receptor-α. In conclusion, pharmacological inhibition of NLRP3 in aged mice has a significant impact on health. Thus, NLRP3 may be a therapeutic target of human age-related metabolic syndrome.

NLRP3 inflammasome suppression improves longevity and prevents cardiac aging in male mice.

While NLRP3-inflammasome has been implicated in cardiovascular diseases, its role in physiological cardiac aging is largely unknown. During aging, many alterations occur in the organism, which are associated with progressive impairment of metabolic pathways related to insulin resistance, autophagy dysfunction, and inflammation. Here, we investigated the molecular mechanisms through which NLRP3 inhibition may attenuate cardiac aging. Ablation of NLRP3-inflammasome protected mice from age-related increased insulin sensitivity, reduced IGF-1 and leptin/adiponectin ratio levels, and reduced cardiac damage with protection of the prolongation of the age-dependent PR interval, which is associated with atrial fibrillation by cardiovascular aging and reduced telomere shortening. Furthermore, old NLRP3 KO mice showed an inhibition of the PI3K/AKT/mTOR pathway and autophagy improvement, compared with old wild mice and preserved Nampt-mediated NAD+ levels with increased SIRT1 protein expression. These findings suggest that suppression of NLRP3 prevented many age-associated changes in the heart, preserved cardiac function of aged mice and increased lifespan.

Pangenome of Acinetobacter baumannii uncovers two groups of genomes, one of them with genes involved in CRISPR/Cas defence systems associated with the absence of plasmids and exclusive genes for biofilm formation.

Acinetobacter baumannii is an opportunistic bacterium that causes hospital-acquired infections with a high mortality and morbidity, since there are strains resistant to virtually any kind of antibiotic. The chase to find novel strategies to fight against this microbe can be favoured by knowledge of the complete catalogue of genes of the species, and their relationship with the specific characteristics of different isolates. In this work, we performed a genomics analysis of almost 2500 strains. Two different groups of genomes were found based on the number of shared genes. One of these groups rarely has plasmids, and bears clustered regularly interspaced short palindromic repeat (CRISPR) sequences, in addition to CRISPR-associated genes (cas genes) or restriction-modification system genes. This fact strongly supports the lack of plasmids. Furthermore, the scarce plasmids in this group also bear CRISPR sequences, and specifically contain genes involved in prokaryotic toxin-antitoxin systems that could either act as the still little known CRISPR type IV system or be the precursors of other novel CRISPR/Cas systems. In addition, a limited set of strains present a new cas9-like gene, which may complement the other cas genes in inhibiting the entrance of new plasmids into the bacteria. Finally, this group has exclusive genes involved in biofilm formation, which would connect CRISPR systems to the biogenesis of these bacterial resistance structures.