Classification of Neisseria meningitidis genomes with a bag-of-words approach and machine learning.

Whole genome sequencing of bacteria is important to enable strain classification. Using entire genomes as an input to machine learning (ML) models would allow rapid classification of strains while using information from multiple genetic elements. We developed a "bag-of-words" approach to encode, using SentencePiece or k-mer tokenization, entire bacterial genomes and analyze these with ML. Initial model selection identified SentencePiece with 8,000 and 32,000 words as the best approach for genome tokenization. We then classified in Neisseria meningitidis genomes the capsule B group genotype with 99.6% accuracy and the multifactor invasive phenotype with 90.2% accuracy, in an independent test set. Subsequently, in silico knockouts of 2,808 genes confirmed that the ML model predictions aligned with our current understanding of the underlying biology. To our knowledge, this is the first ML method using entire bacterial genomes to classify strains and identify genes considered relevant by the classifier.

A Lean Reverse Vaccinology Pipeline with Publicly Available Bioinformatic Tools.

Reverse vaccinology (RV) marked an outstanding improvement in vaccinology employing bioinformatics tools to extract effective features from protein sequences to drive the selection of potential vaccine candidates (Rappuoli, Curr Opin Microbiol 3(5):445-450, 2000). Pioneered by Rino Rappuoli and first used against serogroup B meningococcus, since then, it has been used on several other bacterial vaccines, varying during time the adopted bioinformatics tools. Based on our experience in the field of RV and following an extensive literature review, we consolidate a lean RV pipeline of publicly available bioinformatic tools whose usage is described in this contribution. The protein features, whose extraction is reported in this contribution, can be also the input in a matrix format for machine learning-based approaches.

Bactericidal antibodies against hypervirulent Neisseria meningitidis C field strains following MenC-CRM or MenACWY-CRM priming and MenACWY-CRM booster in children.

An increase in invasive meningococcal disease (IMD) incidence was observed in Tuscany in 2015/2016, mainly due to hypervirulent clonal complex (cc) 11 strains. In a post-hoc analysis, we assessed bactericidal activity of antibodies in sera from children primed with MenACWY-CRM or MenC-CRM conjugate vaccines and receiving a MenACWY-CRM booster dose against 5 meningococcal C (MenC) strains isolated from IMD cases. Sera collected from 90 infants/toddlers who participated in a phase III, open-label study (NCT00667602) and its extension (NCT01345721) were tested by serum bactericidal activity assay with human complement (hSBA). Children were primed with either MenACWY-CRM at 6-8 and 12 months of age (group 2_MenACWY; N = 30), MenACWY-CRM (group 1_MenACWY; N = 30), or MenC-CRM at 12 months of age (group 1_MenC; N = 30); all received MenACWY-CRM booster dose at 22-45 months of age. Four tested strains (FI001-FI004) were C:P1.5-1,10-8:F3-6:ST-11 (cc11) and 1 (FI005) was C:P1.7-4,14-6:F3-9:ST-1031 (cc334). Overall, immune responses tended to be higher against Fl002-FI004 than Fl001 and Fl005. Geometric mean titers were high in group 2_MenACWY (range: 94.8 [FI005]-588.1 [FI004]) and very high post-boosting with MenACWY-CRM in all groups (176.9 [FI005]-3911.0 [FI004]). Seroresponse rates tended to be higher in group 1_MenC (33.3% [FI005]-93.3% [FI004]) than in group 1_MenACWY (16.7% [FI005]-73.3% [FI004]). Irrespective of strains tested or the identity/number of priming doses, ≥96.7% of children had hSBA titers ≥1:8 post-MenACWY-CRM booster dose. MenACWY-CRM and MenC-CRM elicited bactericidal antibodies and immunological memory against hypervirulent cc11 and cc334 MenC strains responsible for IMD outbreaks.

Genomic Characterization of Invasive Meningococcal Serogroup B Isolates and Estimation of 4CMenB Vaccine Coverage in Finland.

Invasive meningococcal disease (IMD) caused by Neisseria meningitidis is a significant cause of morbidity and mortality worldwide. In Finland, the incidence rate of IMD is low, with meningococcal serogroup B (MenB) accounting for around one-third of IMD cases annually. The aim of this study was to investigate the genetic variability of invasive MenB isolates collected in Finland between 2010 and 2017 (n = 81), including the genes encoding the 4-component MenB vaccine (4CMenB; Bexsero; GSK) antigens and their promoters, and to evaluate the 4CMenB potential coverage. Whole-genome sequencing was performed. The meningococcal antigen typing system (MATS) was used to characterize MenB isolates and predict the potential coverage of 4CMenB. MATS was complemented by genetic MATS (gMATS) through association of antigen genotyping and phenotypic MATS results. Multilocus sequence typing revealed predominance of the ST-41/44 clonal complex among which sequence type (ST)-303 was the most common and was predicted to be covered by 4CMenB. Of the 4 major vaccine antigens, the factor H-binding protein variant 1, neisserial heparin binding antigen peptide 2, and the PorA P1.4 antigen were predominant, whereas Neisseria adhesin A was present in only 4% of the 81 isolates. MATS and gMATS 4CMenB strain coverage predictions were 78% and 86%, respectively, in a subpanel of 60 isolates collected during 2010 to 2014, with a gMATS prediction of 84% for all 81 isolates. The results suggest that 4CMenB could reduce the burden of IMD in Finland and that gMATS could be applied to monitor vaccine strain coverage and predict vaccine effectiveness.IMPORTANCE 4CMenB is a 4-component vaccine used against invasive meningococcal disease (IMD) caused by Neisseria meningitidis serogroup B (MenB). We investigated the genetic variability of MenB in Finland and evaluated 4CMenB strain coverage by 2 different methods: MATS (meningococcal antigen typing system) and gMATS (genetic MATS). In a set of MenB isolates, 78% (MATS) and 86% (gMATS) were predicted as covered by 4CMenB, suggesting that use of 4CMenB would help reduce IMD incidence in Finland. MATS has been used in 13 countries worldwide, generating information on phenotypic characteristics that could infer protection by 4CMenB. Based on these data and genetic information, gMATS coverage predictions can be made. gMATS predicts coverage consistent with MATS for about 94% of tested strains. Unlike MATS, gMATS does not require live isolates, thus allowing the analysis also of noncultivable strains, making the coverage predictions more accurate. Therefore, gMATS can replace MATS to assess 4CMenB coverage, including in regions with no prior MATS data.

STRAIN: an R package for multi-locus sequence typing from whole genome sequencing data.

BACKGROUND: Multi-locus sequence typing (MLST) is a standard typing technique used to associate a sequence type (ST) to a bacterial isolate. When the output of whole genome sequencing (WGS) of a sample is available the ST can be assigned directly processing the read-set. Current approaches employ reads mapping (SRST2) against the MLST loci, k-mer distribution (stringMLST), selective assembly (GRAbB) or whole genome assembly (BIGSdb) followed by BLASTn sequence query. Here we present STRAIN (ST Reduced Assembly IdentificatioN), an R package that implements a hybrid strategy between assembly and mapping of the reads to assign the ST to an isolate starting from its read-sets. RESULTS: Analysis of 540 publicly accessible Illumina read sets showed STRAIN to be more accurate at correct allele assignment and new alleles identification compared to SRTS2, stringMLST and GRAbB. STRAIN assigned correctly 3666 out of 3780 alleles (capability to identify correct alleles 97%) and, when presented with samples containing new alleles, identified them in 3730 out of 3780 STs (capability to identify new alleles 98.7%) of the cases. On the same dataset the other tested tools achieved lower capability to identify correct alleles (from 28.5 to 96.9%) and lower capability to identify new alleles (from 1.1 to 97.1%). CONCLUSIONS: STRAIN is a new accurate method to assign the alleles and ST to an isolate by processing the raw reads output of WGS. STRAIN is also able to retrieve new allele sequences if present. Capability to identify correct and new STs/alleles, evaluated on a benchmark dataset, are higher than other existing methods. STRAIN is designed for single allele typing as well as MLST. Its implementation in R makes allele and ST assignment simple, direct and prompt to be integrated in wider pipeline of downstream bioinformatics analyses.

Comparison of Open-Source Reverse Vaccinology Programs for Bacterial Vaccine Antigen Discovery.

Reverse Vaccinology (RV) is a widely used approach to identify potential vaccine candidates (PVCs) by screening the proteome of a pathogen through computational analyses. Since its first application in Group B meningococcus (MenB) vaccine in early 1990's, several software programs have been developed implementing different flavors of the first RV protocol. However, there has been no comprehensive review to date on these different RV tools. We have compared six of these applications designed for bacterial vaccines (NERVE, Vaxign, VaxiJen, Jenner-predict, Bowman-Heinson, and VacSol) against a set of 11 pathogens for which a curated list of known bacterial protective antigens (BPAs) was available. We present results on: (1) the comparison of criteria and programs used for the selection of PVCs (2) computational runtime and (3) performances in terms of fraction of proteome identified as PVC, fraction and enrichment of BPA identified in the set of PVCs. This review demonstrates that none of the programs was able to recall 100% of the tested set of BPAs and that the output lists of proteins are in poor agreement suggesting in the process of prioritize vaccine candidates not to rely on a single RV tool response. Singularly the best balance in terms of fraction of a proteome predicted as good candidate and recall of BPAs has been observed by the machine-learning approach proposed by Bowman (1) and enhanced by Heinson (2). Even though more performing than the other approaches it shows the disadvantage of limited accessibility to non-experts users and strong dependence between results and a-priori training dataset composition. In conclusion we believe that to significantly enhance the performances of next RV methods further studies should focus on the enhancement of accuracy of the existing protein annotation tools and should leverage on the assets of machine-learning techniques applied to biological datasets expanded also through the incorporation and curation of bacterial proteins characterized by negative experimental results.

Genetic Meningococcal Antigen Typing System (gMATS): A genotyping tool that predicts 4CMenB strain coverage worldwide.

BACKGROUND: The Meningococcal Antigen Typing System (MATS) was developed to identify meningococcus group B strains with a high likelihood of being covered by the 4CMenB vaccine, but is limited by the requirement for viable isolates from culture-confirmed cases. We examined if antigen genotyping could complement MATS in predicting strain coverage by the 4CMenB vaccine. METHODS: From a panel of 3912 MATS-typed invasive meningococcal disease isolates collected in England and Wales in 2007-2008, 2014-2015 and 2015-2016, and in 16 other countries in 2000-2015, 3481 isolates were also characterized by antigen genotyping. Individual associations between antigen genotypes and MATS coverage for each 4CMenB component were used to define a genetic MATS (gMATS). gMATS estimates were compared with England and Wales human complement serum bactericidal assay (hSBA) data and vaccine effectiveness (VE) data from England. RESULTS: Overall, 81% of the strain panel had genetically predictable MATS coverage, with 92% accuracy and highly concordant results across national panels (Lin's accuracy coefficient, 0.98; root-mean-square deviation, 6%). England and Wales strain coverage estimates were 72-73% by genotyping (66-73% by MATS), underestimating hSBA values after four vaccine doses (88%) and VE after two doses (83%). The gMATS predicted strain coverage in other countries was 58-88%. CONCLUSIONS: gMATS can replace MATS in predicting 4CMenB strain coverage in four out of five cases, without requiring a cultivable isolate, and is open to further improvement. Both methods underestimated VE in England. Strain coverage predictions in other countries matched or exceeded England and Wales estimates.

Oncogenic H-Ras up-regulates acid ß-hexosaminidase by a mechanism dependent on the autophagy regulator TFEB.

The expression of constitutively active H-RasV12 oncogene has been described to induce proliferative arrest and premature senescence in many cell models. There are a number of studies indicating an association between senescence and lysosomal enzyme alterations, e.g. lysosomal ß-galactosidase is the most widely used biomarker to detect senescence in cultured cells and we previously reported that H-RasV12 up-regulates lysosomal glycohydrolases enzymatic activity in human fibroblasts. Here we investigated the molecular mechanisms underlying lysosomal glycohydrolase ß-hexosaminidase up-regulation in human fibroblasts expressing the constitutively active H-RasV12. We demonstrated that H-Ras activation increases ß-hexosaminidase expression and secretion by a Raf/extracellular signal-regulated protein kinase dependent pathway, through a mechanism that relies on the activity of the transcription factor EB (TFEB). Because of the pivotal role of TFEB in the regulation of lysosomal system biogenesis and function, our results suggest that this could be a general mechanism to enhance lysosomal enzymes activity during oncogene-induced senescence.

Therapeutic approaches for lysosomal storage diseases: a patent update.

Lysosomal Storage Diseases (LSDs) are inherited metabolic disorders caused by specific lysosomal protein deficiencies, which lead to abnormal storage of macromolecular substrates. Most LSDs are characterized by central nervous system (CNS) pathology, intracellular deposition and protein aggregation, events also found in age-related neurodegenerative diseases. Over the past two decades, a few approaches for the cure of these disorders have been approved for clinical use, i.e. enzyme replacement therapy (ERT) and substrate reduction therapy (SRT). However, these treatments are hampered by major limitations, such as the poor biodistribution in the CNS for ERT and severe side effects for SRT. Several additional therapeutic strategies have been proposed. In particular clinical trials are ongoing based on enzyme enhancement by pharmacological chaperones, i.e. small molecule compounds able to increases the residual activity of the lysosomal enzyme, and gene therapy approaches. In addition, recent patents in the field provide evidence that many efforts are currently dedicated to i) improve the properties of enzymes used for ERT, ii) find new pharmacological chaperones without inhibitory effects on enzyme activity and iii) combine gene therapy approaches with genome editing methods.

hLGDB: a database of human lysosomal genes and their regulation.

Lysosomes are cytoplasmic organelles present in almost all eukaryotic cells, which play a fundamental role in key aspects of cellular homeostasis such as membrane repair, autophagy, endocitosis and protein metabolism. The characterization of the genes and enzymes constituting the lysosome represents a central issue to be addressed toward a better understanding of the biology of this organelle. In humans, mutations that cause lysosomal enzyme deficiencies result in >50 different disorders and severe pathologies. So far, many experimental efforts using different methodologies have been carried out to identity lysosomal genes. The Human Lysosome Gene Database (hLGDB) is the first resource that provides a comprehensive and accessible census of the human genes belonging to the lysosomal system. This database was developed by collecting and annotating gene lists from many different sources. References to the studies that have identified each gene are provided together with cross databases gene related information. Special attention has been given to the regulation of the genes through microRNAs and the transcription factor EB. The hLGDB can be easily queried to retrieve, combine and analyze information on different lists of lysosomal genes and their regulation by microRNA (binding sites predicted by five different algorithms). The hLGDB is an open access dynamic project that will permit in the future to collapse in a unique publicly accessible resource all the available biological information about lysosome genes and their regulation. Database URL: http://lysosome.unipg.it/.

Signaling pathways in exosomes biogenesis, secretion and fate.

Exosomes are small extracellular vesicles (30-100 nm) derived from the endosomal system, which have raised considerable interest in the last decade. Several studies have shown that they mediate cell-to-cell communication in a variety of biological processes. Thus, in addition to cell-to-cell direct interaction or secretion of active molecules, they are now considered another class of signal mediators. Exosomes can be secreted by several cell types and retrieved in many body fluids, such as blood, urine, saliva and cerebrospinal fluid. In addition to proteins and lipids, they also contain nucleic acids, namely mRNA and miRNA. These features have prompted extensive research to exploit them as a source of biomarkers for several pathologies, such as cancer and neurodegenerative disorders. In this context, exosomes also appear attractive as gene delivery vehicles. Furthermore, exosome immunomodulatory and regenerative properties are also encouraging their application for further therapeutic purposes. Nevertheless, several issues remain to be addressed: exosome biogenesis and secretion mechanisms have not been clearly understood, and physiological functions, as well as pathological roles, are far from being satisfactorily elucidated.

Array-based genotyping in S.cerevisiae using semi-supervised clustering.

MOTIVATION: Microarrays provide an accurate and cost-effective method for genotyping large numbers of individuals at high resolution. The resulting data permit the identification of loci at which genetic variation is associated with quantitative traits, or fine mapping of meiotic recombination, which is a key determinant of genetic diversity among individuals. Several issues inherent to short oligonucleotide arrays -- cross-hybridization, or variability in probe response to target -- have the potential to produce genotyping errors. There is a need for improved statistical methods for array-based genotyping. RESULTS: We developed ssGenotyping (ssG), a multivariate, semi-supervised approach for using microarrays to genotype haploid individuals at thousands of polymorphic sites. Using a meiotic recombination dataset, we show that ssG is more accurate than existing supervised classification methods, and that it produces denser marker coverage. The ssG algorithm is able to fit probe-specific affinity differences and to detect and filter spurious signal, permitting high-confidence genotyping at nucleotide resolution. We also demonstrate that oligonucleotide probe response depends significantly on genomic background, even when the probe's specific target sequence is unchanged. As a result, supervised classifiers trained on reference strains may not generalize well to diverged strains; ssG's semi-supervised approach, on the other hand, adapts automatically.

CARPET: a web-based package for the analysis of ChIP-chip and expression tiling data.

SUMMARY: CARPET (collection of automated routine programs for easy tiling) is a set of Perl, Python and R scripts, integrated on the Galaxy2 web-based platform, for the analysis of ChIP-chip and expression tiling data, both for standard and custom chip designs. CARPET allows rapid experimental data entry, simple quality control, normalization, easy identification and annotation of enriched ChIP-chip regions, detection of the absolute or relative transcriptional status of genes assessed by expression tiling experiments and, more importantly, it allows the integration of ChIP-chip and expression data. Results can be visualized instantly in a genomic context within the UCSC genome browser as graph-based custom tracks through Galaxy2. All generated and uploaded data can be stored within sessions and are easily shared with other users. AVAILABILITY: http://bio.ifom-ieo-campus.it/galaxy

High-resolution mapping of meiotic crossovers and non-crossovers in yeast.

Meiotic recombination has a central role in the evolution of sexually reproducing organisms. The two recombination outcomes, crossover and non-crossover, increase genetic diversity, but have the potential to homogenize alleles by gene conversion. Whereas crossover rates vary considerably across the genome, non-crossovers and gene conversions have only been identified in a handful of loci. To examine recombination genome wide and at high spatial resolution, we generated maps of crossovers, crossover-associated gene conversion and non-crossover gene conversion using dense genetic marker data collected from all four products of fifty-six yeast (Saccharomyces cerevisiae) meioses. Our maps reveal differences in the distributions of crossovers and non-crossovers, showing more regions where either crossovers or non-crossovers are favoured than expected by chance. Furthermore, we detect evidence for interference between crossovers and non-crossovers, a phenomenon previously only known to occur between crossovers. Up to 1% of the genome of each meiotic product is subject to gene conversion in a single meiosis, with detectable bias towards GC nucleotides. To our knowledge the maps represent the first high-resolution, genome-wide characterization of the multiple outcomes of recombination in any organism. In addition, because non-crossover hotspots create holes of reduced linkage within haplotype blocks, our results stress the need to incorporate non-crossovers into genetic linkage analysis.

Complex Loci in human and mouse genomes.

Mammalian genomes harbor a larger than expected number of complex loci, in which multiple genes are coupled by shared transcribed regions in antisense orientation and/or by bidirectional core promoters. To determine the incidence, functional significance, and evolutionary context of mammalian complex loci, we identified and characterized 5,248 cis-antisense pairs, 1,638 bidirectional promoters, and 1,153 chains of multiple cis-antisense and/or bidirectionally promoted pairs from 36,606 mouse transcriptional units (TUs), along with 6,141 cis-antisense pairs, 2,113 bidirectional promoters, and 1,480 chains from 42,887 human TUs. In both human and mouse, 25% of TUs resided in cis-antisense pairs, only 17% of which were conserved between the two organisms, indicating frequent species specificity of antisense gene arrangements. A sampling approach indicated that over 40% of all TUs might actually be in cis-antisense pairs, and that only a minority of these arrangements are likely to be conserved between human and mouse. Bidirectional promoters were characterized by variable transcriptional start sites and an identifiable midpoint at which overall sequence composition changed strand and the direction of transcriptional initiation switched. In microarray data covering a wide range of mouse tissues, genes in cis-antisense and bidirectionally promoted arrangement showed a higher probability of being coordinately expressed than random pairs of genes. In a case study on homeotic loci, we observed extensive transcription of nonconserved sequences on the noncoding strand, implying that the presence rather than the sequence of these transcripts is of functional importance. Complex loci are ubiquitous, host numerous nonconserved gene structures and lineage-specific exonification events, and may have a cis-regulatory impact on the member genes.