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Clinical case of a patient with aPseudomonas aeruginosamultidrug-resistant prosthetic vascular graft infection which was treated with a cocktail of phages (PT07, 14/01 and PNM) in combination with ceftazidime-avibactam (CAZ/AVI). After the application of the phage treatment and in absence of antimicrobial therapy, a newP. aeruginosabloodstream infection (BSI) with a septic residual limb metastasis occurred, now involving a wild-type strain being susceptible to ß-lactams and quinolones. Clinical strains were analyzed by microbiology and whole genome sequencing techniques. In relation with phage administration, the clinical isolates ofP. aeruginosabefore phage therapy (HE2011471) and post phage therapy (HE2105886) showed a clonal relationship but with important genomic changes which could be involved in the resistance to this therapy. Finally, phenotypic studies showed a decreased in Minimum Inhibitory Concentration (MIC) to ß-lactams and quinolones as well as an increase of the biofilm production and phage resistant mutants in the clinical isolate ofP. aeruginosapost phage therapy.ImportancePhage therapy is a promising new treatment against infections produced by multi-drug resistant pathogens. For that, it would be necessary to know more about the clinical response and host-phage interactions by massive sequencing techniques to improve phage therapy application. In this work, we analyzed the clinical, microbiological and molecular features of theP. aeruginosaisolates in prosthetic vascular graft infection after the phages administration failure against this infection. This knowledge could allow to develop strategies of improvement of the use of phage therapy as treatment of multiple clinical infections.

Background Seven CTX-M-27-producing Shigella sonnei strains were isolated at the University Hospital Virgen del Rocío (Seville, Spain) microbiology service from October to November 2021. Objectives To offer extensive information on the microbiological and molecular epidemiology results of the seven S. sonnei isolates and compare them with other previously documented CTX-M-27-producing S. sonnei associated with MSM transmission. Methods S. sonnei isolated from stool samples of patients with acute diarrhoea were identified through biochemical and serological typing. Whole characterization of the seven isolates was performed by sequencing with MinION Mk1C followed by genomic and molecular analysis. Results All the isolates were resistant to penicillins, cephalosporins, fluoroquinolones, cotrimoxazole and azithromycin. Sequencing showed the presence of several resistance determinants, outstanding blaCTX-M-27, azithromycin resistance genes [ermB and mph(A)], qnrB19 and mutations in the QRDRs. All isolates belonged to the same hierarchical clustering of cgMLST (HierCC) with five allele distance (HC5) scheme v1 from EnteroBase. However, they presented differences in plasmid composition, with all seven isolates harbouring IncFII, IncB/O/K/Z and ColE1-like while SH2, SH6 and SH7 had IncFIB only. Our isolates were closely related to others from Spain (HC5; 98748), Australia (HC5; 98748) and the UK (HC5; 98748), which were also associated with MSM transmission. Nevertheless, the structure of the non-chromosomal genetic elements and the genetic context of blaCTX-M-27 presented a certain variability compared with isolates from other countries and among them. Conclusions This study confirms the emergence of CTX-M-27-producing S. sonnei (ST152) associated with MSM transmission in Spain, adding it to the Europe outbreak list and reinforcing the necessity of active surveillance and control of this high-risk clone.

© The Author(s) 2020., [Motivation]: Short bioactive peptides encoded by small open reading frames (sORFs) play important roles in eukaryotes. Bioinformatics prediction of ORFs is an early step in a genome sequence analysis, but sORFs encoding short peptides, often using non-AUG initiation codons, are not easily discriminated from false ORFs occurring by chance., [Results]: AnABlast is a computational tool designed to highlight putative protein-coding regions in genomic DNA sequences. This protein-coding finder is independent of ORF length and reading frame shifts, thus making of AnABlast a potentially useful tool to predict sORFs. Using this algorithm, here, we report the identification of 82 putative new intergenic sORFs in the Caenorhabditis elegans genome. Sequence similarity, motif presence, expression data and RNA interference experiments support that the underlined sORFs likely encode functional peptides, encouraging the use of AnABlast as a new approach for the accurate prediction of intergenic sORFs in annotated eukaryotic genomes., [Availability and implementation]: AnABlast is freely available at http://www.bioinfocabd.upo.es/ab/. The C.elegans genome browser with AnABlast results, annotated genes and all data used in this study is available at http://www.bioinfocabd.upo.es/celegans., This research was supported by the Ministry of Economy and Competitiveness of the Spanish Government [BFU2016-77297-P].

Seven CTX-M-27-producingTo offer extensive information on the microbiological and molecular epidemiology results of the sevenAll the isolates were resistant to penicillins, cephalosporins, fluoroquinolones, cotrimoxazole and azithromycin. Sequencing showed the presence of several resistance determinants, outstandingThis study confirms the emergence of CTX-M-27-producing

Gut microbiome is gaining interest because of its links with several diseases, including colorectal cancer (CRC), as well as the possibility of being used to obtain non-intrusive predictive disease biomarkers. Here we performed a meta-analysis of 1042 fecal metagenomic samples from seven publicly available studies. We used an interpretable machine learning approach based on functional profiles, instead of the conventional taxonomic profiles, to produce a highly accurate predictor of CRC with better precision than those of previous proposals. Moreover, this approach is also able to discriminate samples with adenoma, which makes this approach very promising for CRC prevention by detecting early stages in which intervention is easier and more effective. In addition, interpretable machine learning methods allow extracting features relevant for the classification, which reveals basic molecular mechanisms accounting for the changes undergone by the microbiome functional landscape in the transition from healthy gut to adenoma and CRC conditions. Functional profiles have demonstrated superior accuracy in predicting CRC and adenoma conditions than taxonomic profiles and additionally, in a context of explainable machine learning, provide useful hints on the molecular mechanisms operating in the microbiota behind these conditions., This work is supported by Grants PID2020-117979RB-I00 from the Spanish Ministry of Science and Innovation and PI20/01305 and IMP/0019 from the ISCIII, both co-funded with European Regional Development Funds (ERDF) as well as H2020 Programme of the European Union Grants Marie Curie Innovative Training Network "Machine Learning Frontiers in Precision Medicine" (MLFPM) (GA 813533) and “ELIXIR-EXCELERATE fast-track ELIXIR implementation and drive early user exploitation across the life sciences” (GA 676559). The postdoctoral contract for CL PAIDI2020- DOC_00350 is funded by Junta de Andalucía and co-funded by the European Social Fund (FSE) 2014-2020.

Backgroundthe current SARS-CoV-2 pandemic has emphasized the utility of viral whole genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is increasingly producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and therefore useless, sequences. However, viral sequences evolve in the context of a complex phylogeny and therefore different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data.ResultsWe developed impuSARS, an application that includes Minimac, the most widely used strategy for genomic data imputation and, taking advantage of the enormous amount of SARS-CoV-2 whole genome sequences available, a reference panel containing 239,301 sequences was built. The impuSARS application was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing) showing great fidelity when reconstructing the original sequences. The impuSARS application is also able to impute whole genomes from commercial kits covering less than 20% of the genome or only from theSpikeprotein with a precision of 0.96. It also recovers the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (< 20%)Conclusionsimputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. impuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole genome sequencing.

[Background] Hirschsprung disease (HSCR, OMIM 142623) is a rare congenital disorder that results from a failure to fully colonize the gut by enteric precursor cells (EPCs) derived from the neural crest. Such incomplete gut colonization is due to alterations in EPCs proliferation, survival, migration and/or differentiation during enteric nervous system (ENS) development. This complex process is regulated by a network of signaling pathways that is orchestrated by genetic and epigenetic factors, and therefore alterations at these levels can lead to the onset of neurocristopathies such as HSCR. The goal of this study is to broaden our knowledge of the role of epigenetic mechanisms in the disease context, specifically in DNA methylation. Therefore, with this aim, a Whole-Genome Bisulfite Sequencing assay has been performed using EPCs from HSCR patients and human controls., [Results] This is the first study to present a whole genome DNA methylation profile in HSCR and reveal a decrease of global DNA methylation in CpG context in HSCR patients compared with controls, which correlates with a greater hypomethylation of the differentially methylated regions (DMRs) identified. These results agree with the de novo Methyltransferase 3b downregulation in EPCs from HSCR patients compared to controls, and with the decrease in the global DNA methylation level previously described by our group. Through the comparative analysis of DMRs between HSCR patients and controls, a set of new genes has been identified as potential susceptibility genes for HSCR at an epigenetic level. Moreover, previous differentially methylated genes related to HSCR have been found, which validates our approach., [Conclusions] This study highlights the relevance of an adequate methylation pattern for a proper ENS development. This is a research area that provides a novel approach to deepen our understanding of the etiopathogenesis of HSCR., This work was supported by Instituto de Salud Carlos III through the Projects [PI16/0142, PI19/01550] (co-funded by the European Regional Development Fund/European Social Fund, "A way to make Europe"/"Investing in your future"); and by the Regional Ministry of Health and Family of the Regional Government of Andalusia [PEER-0470–2019]. L.V.-B. was supported by a fellowship associated with the CTS-7447 Project, which has been funded by the Regional Ministry of Innovation, Science and Enterprise of the Regional Government of Andalusia.

Background Gut microbiome is gaining interest because its links with several diseases, including colorectal cancer (CRC). Results Here we performed a meta-analysis of 851 fecal metagenomic samples from five publicly available studies. We used an interpretable machine learning approach based on functional profiles, instead of the conventional taxonomic profiles, to produce a highly accurate predictor of CRC with better precision than those of previous proposals. Moreover, this approach is also able to discriminate samples with adenoma, which makes this approach very promising for CRC prevention by detecting early stages in which intervention is easier and more effective. In addition, interpretable machine learning methods allows extracting features relevant for the classification, which reveals basic molecular mechanisms accounting for the changes underwent by the microbiome functional landscape in the transition from healthy gut to adenoma and CRC conditions. Conclusion Functional profiles provide superior accuracy in predicting CCR and adenoma conditions than taxonomic profiles and additionally, in a context of explainable machine learning, provide useful hints on the molecular mechanisms operating in the microbiota behind these conditions.

[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., This research was supported by the Ministry of Economy and Competitiveness of the Spanish Government grant BFU2016–77297-P. It has funded the PhD thesis of CC and the project where this article is integrated.

AnABlast is a computational tool that highlights protein-coding regions within intergenic and intronic DNA sequences which escape detection by standard gene prediction algorithms. DNA sequences with small protein-coding genes or exons, complex intron-containing genes, or degenerated DNA fragments are efficiently targeted by AnABlast. Furthermore, this algorithm is particularly useful in detecting protein-coding sequences with nonsignificant homologs to sequences in databases. AnABlast can be executed online at http://www.bioinfocabd.upo.es/anablast/ .

3 Páginas.-- 1 Tabla, The draft genome sequences of five Lactobacillus pentosus strains isolated from biofilms on the skin of green table olives are presented here. These genome sequences will assist in revealing the potential probiotic properties of these strains, as the intake of fermented olives implicates the passage of millions of Lactobacillus spp. throughout a consumer’s gastrointestinal tract., This work was funded by the Junta de Andalucía through the P11-AGR-7051 project and by the Spanish Government through MICIIN projects AGL2013-48300-R/ALI (OliFilm project: www.olifilm.science.com.es) and BFU2016-77297-P. B.C.-D. was the beneficiary of a PIF grant from the Junta de Andalucía, and A.B.-C. was supported by the MICIIN through a PIF grant. We thank C3UPO for the high-performance computing (HPC) support.

AnABlast is a computational tool that highlights protein-coding regions within intergenic and intronic DNA sequences which escape detection by standard gene prediction algorithms. DNA sequences with small protein-coding genes or exons, complex intron-containing genes, or degenerated DNA fragments are efficiently targeted by AnABlast. Furthermore, this algorithm is particularly useful in detecting protein-coding sequences with nonsignificant homologs to sequences in databases. AnABlast can be executed online at http://www.bioinfocabd.upo.es/anablast/ .

Here, we report the genome sequences of six Lactobacillus pentosus strains isolated from traditional noninoculated Spanish-style green table olive brines. The total genome sizes varied between 3.77 and 4.039 Mbp. These genome sequences will assist in revealing the genes responsible for both technological and probiotic properties of these strains., The Junta de Andalucía supported this study through the P11-AGR-7051 project and the Spanish Government through MICIIN projects AGL2013-48300-R/ALI (OliFilm project) and BFU2016-77297-P. B.C.-D. was the beneficiary of a PIF grant from the Junta de Andalucía. We thank C3UPO for the HPC support.

The current cheapening of next-generation sequencing has led to an enormous growth in the number of sequenced genomes and transcriptomes, allowing wet labs to get the sequences from their organisms of study. To make the most of these data, one of the first things that should be done is the functional annotation of the protein-coding genes. But it used to be a slow and tedious step that can involve the characterization of thousands of sequences. Sma3s is an accurate computational tool for annotating proteins in an unattended way. Now, we have developed a completely new version, which includes functionalities that will be of utility for fundamental and applied science. Currently, the results provide functional categories such as biological processes, which become useful for both characterizing particular sequence datasets and comparing results from different projects. But one of the most important implemented innovations is that it has now low computational requirements, and the complete annotation of a simple proteome or transcriptome usually takes around 24 hours in a personal computer. Sma3s has been tested with a large amount of complete proteomes and transcriptomes, and it has demonstrated its potential in health science and other specific projects., This research was supported by the Ministry of Economy and Competitiveness of the Spanish Government grant BFU2013-46923-P.

et al., Lactobacillus pentosus MP-10 is a potential probiotic lactic acid bacterium originally isolated from naturally fermented Aloreña green table olives. The entire genome sequence was annotated to in silico analyze the molecular mechanisms involved in the adaptation of L. pentosus MP-10 to the human gastrointestinal tract (GIT), such as carbohydrate metabolism (related with prebiotic utilization) and the proteins involved in bacteria-host interactions. We predicted an arsenal of genes coding for carbohydrate-modifying enzymes to modify oligo- and polysaccharides, such as glycoside hydrolases, glycoside transferases, and isomerases, and other enzymes involved in complex carbohydrate metabolism especially starch, raffinose, and levan. These enzymes represent key indicators of the bacteria's adaptation to the GIT environment, since they involve the metabolism and assimilation of complex carbohydrates not digested by human enzymes. We also detected key probiotic ligands (surface proteins, excreted or secreted proteins) involved in the adhesion to host cells such as adhesion to mucus, epithelial cells or extracellular matrix, and plasma components; also, moonlighting proteins or multifunctional proteins were found that could be involved in adhesion to epithelial cells and/or extracellular matrix proteins and also affect host immunomodulation. In silico analysis of the genome sequence of L. pentosus MP-10 is an important initial step to screen for genes encoding for proteins that may provide probiotic features, and thus provides one new routes for screening and studying this potentially probiotic bacterium., We acknowledge research grants AGL2013-43571-P (Ministerio de Economía y Competitividad, MINECO, FEDER), UJA2014/07/02 (Plan Propio UJA) and Research Team (EI_BIO01_2017).

et al., Analysis of repetitive DNA sequence content and divergence among the repetitive functional classes is a well-accepted approach for estimation of inter- and intra-generic differences in plant genomes. Among these elements, microsatellites, or Simple Sequence Repeats (SSRs), have been widely demonstrated as powerful genetic markers for species and varieties discrimination. We present PlantFuncSSRs platform having more than 364 plant species with more than 2 million functional SSRs. They are provided with detailed annotations for easy functional browsing of SSRs and with information on primer pairs and associated functional domains. PlantFuncSSRs can be leveraged to identify functional-based genic variability among the species of interest, which might be of particular interest in developing functional markers in plants. This comprehensive on-line portal unifies mining of SSRs from first and next generation sequencing datasets, corresponding primer pairs and associated in-depth functional annotation such as gene ontology annotation, gene interactions and its identification from reference protein databases., Gaurav Sablok thanks Plant Functional Biology and Climate Change Cluster (C3), University of Technology Sydney, PO Box 123, Broadway, NSW 2007, Australia, for providing the computational facilities. An internal grant number to GS (2226018) supported this work. JAH and TYS were partially supported by High Impact Research Chancellory Grant UM.C/625/1/HIR/MOHE/SCI/19 from the University of Malaya.