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We investigated whether a set of phylogeographical tracked emergent events of Orthocoronavirinae were related to developed, urban and polluted environments worldwide. We explored coronavirus records in response to climate (rainfall parameters), population density, CO2 emission, Human Developmental Index (HDI) and deforestation. We contrasted environmental characteristics from regions with spillovers or encounters of wild Orthocoronavirinae against adjacent areas having best-preserved conditions. We used all complete sequenced CoVs genomes deposited in NCBI and GISAID databases until January 2021. Except for Deltacoronavirus, concentrated in Hong Kong and in birds, the other three genera were scattered all over the planet, beyond the original distribution of the subfamily, and found in humans, mammals, fishes and birds, wild or domestic. Spillovers and presence in wild animals were only reported in developed/densely populated places. We found significantly more occurrences reported in places with higher HDI, CO2 emission, or population density, along with more rainfall and more accentuated seasonality. Orthocoronavirinae occurred in areas with significantly higher human populations, CO2 emissions and deforestation rates than in adjacent locations. Intermediately disturbed ecosystems seemed more vulnerable for Orthocoronavirinae emergence than forested regions in frontiers of deforestation. Sadly, people experiencing poverty in an intensely consumerist society are the most vulnerable.

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Acinetobacter baumannii is an important Gram-negative opportunistic pathogen that is responsible for many nosocomial infections. This etiologic agent has acquired, over the years, multiple mechanisms of resistance to a wide range of antimicrobials and the ability to survive in different environments. In this context, our study aims to elucidate the resistome from the A. baumannii strains based on phylogenetic, phylogenomic, and comparative genomics analyses. In silico analysis of the complete genomes of A. baumannii strains was carried out to identify genes involved in the resistance mechanisms and the phylogenetic relationships and grouping of the strains based on the sequence type. The presence of genomic islands containing most of the resistance gene repertoire indicated high genomic plasticity, which probably enabled the acquisition of resistance genes and the formation of a robust resistome. A. baumannii displayed an open pan-genome and revealed a still constant genetic permutation among their strains. Furthermore, the resistance genes suggest a specific profile within the species throughout its evolutionary history. Moreover, the current study performed screening and characterization of the main genes present in the resistome, which can be used in applied research to develop new therapeutic methods to control this important bacterial pathogen.

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The Bifidobacterium longum 51A strain of isolated from feces of a healthy child, has demonstrated probiotic properties by in vivo and in vitro studies, which may be assigned to its production of metabolites such as acetate. Thus, through the study of comparative genomics, the present work sought to identify unique genes that might be related to the production of acetate. To perform the study, the DNA strain was sequenced using Illumina HiSeq technology, followed by assembly and manual curation of coding sequences. Comparative analysis was performed including 19 complete B. longum genomes available in Genbank/NCBI. In the phylogenetic analysis, the CECT 7210 and 157F strains of B. longum subsp. infantis aggregated within the subsp. longum cluster, suggesting that their taxonomic classification should be reviewed. The strain 51A of B. longum has 26 unique genes, six of which are possibly related to carbohydrate metabolism and acetate production. The phosphoketolase pathway from B. longum 51A showed a difference in acetyl-phosphate production. This result seems to corroborate the analysis of their unique genes, whose presence suggests the strain may use different sources of carbohydrates that allow a greater production of acetate and consequently offer benefits to the host health.

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Mycoplasma genitalium is an obligate intracellular bacterium that is responsible for several sexually transmitted infections, including non-gonococcal urethritis in men and several inflammatory reproductive tract syndromes in women. Here, we applied subtractive genomics and reverse vaccinology approaches for in silico prediction of potential vaccine and drug targets against five strains of M. genitalium. We identified 403 genes shared by all five strains, from which 104 non-host homologous proteins were selected, comprising of 44 exposed/secreted/membrane proteins and 60 cytoplasmic proteins. Based on the essentiality, functionality, and structure-based binding affinity, we finally predicted 19 (14 novel) putative vaccine and 7 (2 novel) candidate drug targets. The docking analysis showed six molecules from the ZINC database as promising drug candidates against the identified targets. Altogether, both vaccine candidates and drug targets identified here may contribute to the future development of therapeutic strategies to control the spread of M. genitalium worldwide.

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The COVID-19 pandemic has infected millions worldwide, leaving a global burden for long-term care of COVID-19 survivors. It is thus imperative to study post-COVID (i.e., short-term) and long-COVID (i.e., long-term) effects, specifically as local and systemic pathophysiological outcomes of other coronavirus-related diseases (such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS)) were well-cataloged. We conducted a comprehensive review of adverse post-COVID health outcomes and potential long-COVID effects. We observed that such adverse outcomes were not localized. Rather, they affected different human systems, including: (i) immune system (e.g., Guillain-Barré syndrome, rheumatoid arthritis, pediatric inflammatory multisystem syndromes such as Kawasaki disease), (ii) hematological system (vascular hemostasis, blood coagulation), (iii) pulmonary system (respiratory failure, pulmonary thromboembolism, pulmonary embolism, pneumonia, pulmonary vascular damage, pulmonary fibrosis), (iv) cardiovascular system (myocardial hypertrophy, coronary artery atherosclerosis, focal myocardial fibrosis, acute myocardial infarction, cardiac hypertrophy), (v) gastrointestinal, hepatic, and renal systems (diarrhea, nausea/vomiting, abdominal pain, anorexia, acid reflux, gastrointestinal hemorrhage, lack of appetite/constipation), (vi) skeletomuscular system (immune-mediated skin diseases, psoriasis, lupus), (vii) nervous system (loss of taste/smell/hearing, headaches, spasms, convulsions, confusion, visual impairment, nerve pain, dizziness, impaired consciousness, nausea/vomiting, hemiplegia, ataxia, stroke, cerebral hemorrhage), (viii) mental health (stress, depression and anxiety). We additionally hypothesized mechanisms of action by investigating possible molecular mechanisms associated with these disease outcomes/symptoms. Overall, the COVID-19 pathology is still characterized by cytokine storm that results to endothelial inflammation, microvascular thrombosis, and multiple organ failures.

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BACKGROUND: Mycobacterium leprae and Mycobacterium lepromatosis are gram-positive bacterial pathogens and the causative agents of leprosy in humans across the world. The elimination of leprosy cannot be achieved by multidrug therapy alone, and highlights the need for new tools and drugs to prevent the emergence of new resistant strains. METHODS: In this study, our contribution includes the prediction of vaccine targets and new putative drugs against leprosy, using reverse vaccinology and subtractive genomics. Six strains of Mycobacterium leprae and Mycobacterium lepromatosis (4 and 2 strains, respectively) were used for comparison taking Mycobacterium leprae strain TN as the reference genome. Briefly, we used a combined reverse vaccinology and subtractive genomics approach. RESULTS: As a result, we identified 12 common putative antigenic proteins as vaccine targets and three common drug targets against Mycobacterium leprae and Mycobacterium lepromatosis. Furthermore, the docking analysis using 28 natural compounds with three drug targets was done. CONCLUSIONS: The bis-naphthoquinone compound Diospyrin (CID 308140) obtained from indigenous plant Diospyros spp. showed the most favored binding affinity against predicted drug targets, which can be a candidate therapeutic target in the future against leprosy.

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BACKGROUND: Lactobacillus crispatus is the dominant species in the vaginal microbiota associated with health and considered a homeostasis biomarker. Interestingly, some strains are even used as probiotics. However, the genetic mechanisms of L. crispatus involved in the control of the vaginal microbiome and protection against bacterial vaginosis (BV) are not entirely known. To further investigate these mechanisms, we sequenced and characterized the first four L. crispatus genomes from vaginal samples from Brazilian women and used genome-wide association study (GWAS) and comparative analyses to identify genetic mechanisms involved in healthy or BV conditions and selective pressures acting in the vaginal microbiome. METHODS: The four genomes were sequenced, assembled using ten different strategies and automatically annotated. The functional characterization was performed by bioinformatics tools comparing with known probiotic strains. Moreover, it was selected one representative strain (L. crispatus CRI4) for in vitro detection of phages by electron microscopy. Evolutionary analysis, including phylogeny, GWAS and positive selection were performed using 46 public genomes strains representing health and BV conditions. RESULTS: Genes involved in probiotic effects such as lactic acid production, hydrogen peroxide, bacteriocins, and adhesin were identified. Three hemolysins and putrescine production were predicted, although these features are also present in other probiotic strains. The four genomes presented no plasmids, but 14 known families insertion sequences and several prophages were detected. However, none of the mobile genetic elements contained antimicrobial resistance genes. The genomes harbor a CRISPR-Cas subtype II-A system that is probably inactivated due to fragmentation of the genes csn2 and cas9. No genomic feature was associated with a health condition, perhaps due to its multifactorial characteristic. Five genes were identified as under positive selection, but the selective pressure remains to be discovered. In conclusion, the Brazilian strains investigated in this study present potential protective properties, although in vitro and in vivo studies are required to confirm their efficacy and safety to be considered for human use.

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A heterogeneous disease such as cancer is activated through multiple pathways and different perturbations. Depending upon the activated pathway(s), the survival of the patients varies significantly and shows different efficacy to various drugs. Therefore, cancer subtype detection using genomics level data is a significant research problem. Subtype detection is often a complex problem, and in most cases, needs multi-omics data fusion to achieve accurate subtyping. Different data fusion and subtyping approaches have been proposed over the years, such as kernel-based fusion, matrix factorization, and deep learning autoencoders. In this paper, we compared the performance of different deep learning autoencoders for cancer subtype detection. We performed cancer subtype detection on four different cancer types from The Cancer Genome Atlas (TCGA) datasets using four autoencoder implementations. We also predicted the optimal number of subtypes in a cancer type using the silhouette score and found that the detected subtypes exhibit significant differences in survival profiles. Furthermore, we compared the effect of feature selection and similarity measures for subtype detection. For further evaluation, we used the Glioblastoma multiforme (GBM) dataset and identified the differentially expressed genes in each of the subtypes. The results obtained are consistent with other genomic studies and can be corroborated with the involved pathways and biological functions. Thus, it shows that the results from the autoencoders, obtained through the interaction of different datatypes of cancer, can be used for the prediction and characterization of patient subgroups and survival profiles.

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The genus Klebsiella comprises species that cause nosocomial and community-acquired infections. A dataset was created to compile the sequence type (ST) and capsule type (K-locus) information predicted for 172 worldwide isolates of Klebsiella spp. whose complete genomes could be retrieved from the GenBank (NCBI) repository. The dataset also includes information related to one multidrug-resistant strain (B31) isolated from a patient who was admitted to an intensive care unit in the Northeast region of Brazil. This strain was phenotypically characterized and submitted to whole-genome sequencing and comparative genomics analysis as we recently reported [1]. The dataset also compiles information on Pathogenicity Islands (PIs), Resistance Islands (RIs) and Miscellaneous Islands (MIS) present in the genome of strain B31. The information provided here may support outbreak prevention policies and future epidemiological studies involving Klebsiella spp.

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The emergence of community acquired infections increases the public health concern on K. pneumoniae and closely related bacteria among which antimicrobial resistance spreads. We report a multidrug-resistant K. pneumoniae isolate, B31, of a patient infected in the community and admitted to an intensive care unit in Northeast Brazil. Antimicrobial susceptibility and genome information were thoroughly investigated to characterize B31 in front of 172 sequenced strains of different countries. Assigned to the Sequence Type 15, which is globally spread, B31 presented extended spectrum beta-lactamase, tigecycline and ciprofloxacin resistance. Genome sequencing revealed most resistance genes being carried by plasmids with high dissemination potential. The absence of main virulence factors, like yersiniabactin and colibactin, apparently suggests a mild pathogenic strain which, on the contrary, persisted and caused severe infection in a previously healthy patient. The present study contributes to unveil the unclear genomic scenario of virulent and multidrug-resistant K. pneumoniae in Brazil.

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Mycobacterium leprae and Mycobacterium lepromatosis are gram-positive bacterial pathogens and the causative agents of leprosy in humans across the world. The elimination of leprosy cannot be achieved by multidrug therapy alone, and highlights the need for new tools and drugs to prevent the emergence of new resistant strains. Methods In this study, our contribution includes the prediction of vaccine targets and new putative drugs against leprosy, using reverse vaccinology and subtractive genomics. Six strains of Mycobacterium leprae and Mycobacterium lepromatosis (4 and 2 strains, respectively) were used for comparison taking Mycobacterium leprae strain TN as the reference genome. Briefly, we used a combined reverse vaccinology and subtractive genomics approach. Results As a result, we identified 12 common putative antigenic proteins as vaccine targets and three common drug targets against Mycobacterium leprae and Mycobacterium lepromatosis. Furthermore, the docking analysis using 28 natural compounds with three drug targets was done. Conclusions The bis-naphthoquinone compound Diospyrin (CID 308140) obtained from indigenous plant Diospyros spp. showed the most favored binding affinity against predicted drug targets, which can be a candidate therapeutic target in the future against leprosy.(AU)

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Mycobacterium leprae and Mycobacterium lepromatosis are gram-positive bacterial pathogens and the causative agents of leprosy in humans across the world. The elimination of leprosy cannot be achieved by multidrug therapy alone, and highlights the need for new tools and drugs to prevent the emergence of new resistant strains. Methods In this study, our contribution includes the prediction of vaccine targets and new putative drugs against leprosy, using reverse vaccinology and subtractive genomics. Six strains of Mycobacterium leprae and Mycobacterium lepromatosis (4 and 2 strains, respectively) were used for comparison taking Mycobacterium leprae strain TN as the reference genome. Briefly, we used a combined reverse vaccinology and subtractive genomics approach. Results As a result, we identified 12 common putative antigenic proteins as vaccine targets and three common drug targets against Mycobacterium leprae and Mycobacterium lepromatosis. Furthermore, the docking analysis using 28 natural compounds with three drug targets was done. Conclusions The bis-naphthoquinone compound Diospyrin (CID 308140) obtained from indigenous plant Diospyros spp. showed the most favored binding affinity against predicted drug targets, which can be a candidate therapeutic target in the future against leprosy.(AU)

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The bacterial strain PO100/5 was isolated from a skin abscess taken from a pig (Sus scrofa domesticus) in the Alentejo region of southern Portugal. It was identified as Corynebacterium pseudotuberculosis using biochemical tests, multiplex PCR and Pulsed Field Gel Electrophoresis. After genome sequencing and rpoB phylogeny, the strain was classified as C. ulcerans. To better understand the taxonomy of this strain and improve identification methods, we compared strain PO100/5 to other publicly available genomes from C. diphtheriae group. Taxonomic analysis reclassified it and three others strains as the recently described C. silvaticum, which have been isolated from wild boar and roe deer in Germany and Austria. The results showed that PO100/5 is the first sequenced genome of a C. silvaticum strain from livestock and a different geographical region, has the unique sequence type ST709, and could be could produce the diphtheriae toxin, along with strain 05-13. Genomic analysis of PO100/5 showed four prophages, and eight conserved genomic islands in comparison to C. ulcerans. Pangenome analysis of 38 C. silvaticum and 76 C. ulcerans genomes suggested that C. silvaticum is a genetically homogeneous species, with 73.6% of its genes conserved and a pangenome near to be closed (α > 0.952). There are 172 genes that are unique to C. silvaticum in comparison to C. ulcerans. Most of these conserved genes are related to nutrient uptake and metabolism, prophages or immunity against them, and could be genetic markers for species identification. Strains PO100/5 (livestock) and KL0182T (wild boar) were predicted to be potential human pathogens. This information may be useful for identification and surveillance of this pathogen.

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Staphylococcus aureus (S. aureus) is a highly versatile Gram-positive bacterium that is carried asymptomatically by up to 30% of healthy people, while being a major cause of healthcare-associated infections, making it a worldwide problem in clinical medicine. The adaptive evolution of S. aureus strains is demonstrated by its remarkable capacity to promptly develop high resistance to multiple antibiotics, thus limiting treatment choice. Nowadays, there is a continuous demand for an alternative to the use of antibiotics for S. aureus infections and a strategy to control the spread or to kill phylogenetically related strains. In this scenario, bacteriocins fit as with a promising and interesting alternative. These molecules are produced by a range of bacteria, defined as ribosomally synthesized peptides with bacteriostatic or bactericidal activity against a wide range of pathogens. This work reviews ascertained the main antibiotic-resistance mechanisms of S. aureus strains and the current, informative content concerning the applicability of the use of bacteriocins overlapping the use of conventional antibiotics in the context of S. aureus infections. Besides, we highlight the possible application of these biomolecules on an industrial scale in future work.

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Corynebacterium pseudotuberculosis is a pathogen of veterinary relevance diseases, being divided into two biovars: equi and ovis; causing ulcerative lymphangitis and caseous lymphadenitis, respectively. The isolation and sequencing of C. pseudotuberculosis biovar ovis strains in the Northern and Northeastern regions of Brazil exhibited the emergence of this pathogen, which causes economic losses to small ruminant producers, and condemnation of carcasses and skins of animals. Through the pan-genomic approach, it is possible to determine and analyze genes that are shared by all strains of a species-the core genome. However, many of these genes do not have any predicted function, being characterized as hypothetical proteins (HP). In this study, we considered 32 C. pseudotuberculosis biovar ovis genomes for the pan-genomic analysis, where were identified 172 HP present in a core genome composed by 1255 genes. We are able to functionally annotate 80 sequences previously characterized as HP through the identification of structural features as conserved domains and families. Furthermore, we analyzed the physicochemical properties, subcellular localization and molecular function. Additionally, through RNA-seq data, we investigated the differential gene expression of the annotated HP. Genes inserted in pathogenicity islands had their virulence potential evaluated. Also, we have analyzed the existence of functional associations for their products based on protein-protein interaction networks, and perform the structural prediction of three targets. Due to the integration of different strategies, this study can underlie deeper in vitro researches in the characterization of these HP and the search for new solutions for combat this pathogen.

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Corynebacterium pseudotuberculosis is a Gram-positive bacterium that causes caseous lymphadenitis, a disease that predominantly affects sheep, goat, cattle, buffalo, and horses, but has also been recognized in other animals. This bacterium generates a severe economic impact on countries producing meat. Gene expression studies using RNA-Seq are one of the most commonly used techniques to perform transcriptional experiments. Computational analysis of such data through reverse-engineering algorithms leads to a better understanding of the genome-wide complexity of gene interactomes, enabling the identification of genes having the most significant functions inferred by the activated stress response pathways. In this study, we identified the influential or causal genes from four RNA-Seq datasets from different stress conditions (high iron, low iron, acid, osmosis, and PH) in C. pseudotuberculosis, using a consensus-based network inference algorithm called miRsigand next identified the causal genes in the network using the miRinfluence tool, which is based on the influence diffusion model. We found that over 50% of the genes identified as influential had some essential cellular functions in the genomes. In the strains analyzed, most of the causal genes had crucial roles or participated in processes associated with the response to extracellular stresses, pathogenicity, membrane components, and essential genes. This research brings new insight into the understanding of virulence and infection by C. pseudotuberculosis.

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BACKGROUND: Spirochetal organisms of the Treponema genus are responsible for causing Treponematoses. Pathogenic treponemes is a Gram-negative, motile, spirochete pathogen that causes syphilis in human. Treponema pallidum subsp. endemicum (TEN) causes endemic syphilis (bejel); T. pallidum subsp. pallidum (TPA) causes venereal syphilis; T. pallidum subsp. pertenue (TPE) causes yaws; and T. pallidum subsp. Ccarateum causes pinta. Out of these four high morbidity diseases, venereal syphilis is mediated by sexual contact; the other three diseases are transmitted by close personal contact. The global distribution of syphilis is alarming and there is an increasing need of proper treatment and preventive measures. Unfortunately, effective measures are limited. RESULTS: Here, the genome sequences of 53 T. pallidum strains isolated from different parts of the world and a diverse range of hosts were comparatively analysed using pan-genomic strategy. Phylogenomic, pan-genomic, core genomic and singleton analysis disclosed the close connection among all strains of the pathogen T. pallidum, its clonal behaviour and showed increases in the sizes of the pan-genome. Based on the genome plasticity analysis of the subsets containing the subspecies T pallidum subsp. pallidum, T. pallidum subsp. endemicum and T. pallidum subsp. pertenue, we found differences in the presence/absence of pathogenicity islands (PAIs) and genomic islands (GIs) on subsp.-based study. CONCLUSIONS: In summary, we identified four pathogenicity islands (PAIs), eight genomic islands (GIs) in subsp. pallidum, whereas subsp. endemicum has three PAIs and seven GIs and subsp. pertenue harbours three PAIs and eight GIs. Concerning the presence of genes in PAIs and GIs, we found some genes related to lipid and amino acid biosynthesis that were only present in the subsp. of T. pallidum, compared to T. pallidum subsp. endemicum and T. pallidum subsp. pertenue.

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Background: SARS-CoV-2 is the causal agent of the current coronavirus disease 2019 (COVID-19) pandemic. They are enveloped, positive-sense, single-stranded RNA viruses of the Coronaviridae family. Proteases of SARS-CoV-2 are necessary for viral replication, structural assembly, and pathogenicity. The approximately 33.8 kDa M pro protease of SARS-CoV-2 is a non-human homologue and is highly conserved among several coronaviruses, indicating that M pro could be a potential drug target for Coronaviruses. Methods: Herein, we performed computational ligand screening of four pharmacophores (OEW, remdesivir, hydroxychloroquine and N3) that are presumed to have positive effects against SARS-CoV-2 M pro protease (6LU7), and also screened 50,000 natural compounds from the ZINC Database dataset against this protease target. Results: We found 40 pharmacophore-like structures of natural compounds from diverse chemical classes that exhibited better affinity of docking as compared to the known ligands. The 11 best selected ligands, namely ZINC1845382, ZINC1875405, ZINC2092396, ZINC2104424, ZINC44018332, ZINC2101723, ZINC2094526, ZINC2094304, ZINC2104482, ZINC3984030, and ZINC1531664, are mainly classified as beta-carboline, alkaloids, and polyflavonoids, and all displayed interactions with dyad CYS145 and HIS41 from the protease pocket in a similar way as other known ligands. Conclusions: Our results suggest that these 11 molecules could be effective against SARS-CoV-2 protease and may be subsequently tested in vitro and in vivo to develop novel drugs against this virus.

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The number of draft genomes deposited in Genbank from the National Center for Biotechnology Information (NCBI) is higher than the complete ones. Draft genomes are assemblies that contain fragments of misassembled regions (gaps). Such draft genomes present a hindrance to the complete understanding of the biology and evolution of the organism since they lack genomic information. To overcome this problem, strategies to improve the assembly process are developed continuously. Also, the greatest challenge to the assembly progress is the presence of repetitive DNA regions. This article highlights the use of optical mapping, to detect and correct assembly errors in Corynebacterium pseudotuberculosis. We also demonstrate that choosing a reference genome should be done with caution to avoid assembly errors and loss of genetic information.

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Pneumonia is an infectious disease caused by bacteria, viruses or fungi that results in millions of deaths globally. Despite the existence of prophylactic methods against some of the major pathogens of the disease, there is no efficient prophylaxis against atypical agents such as Mycoplasma pneumoniae, a bacterium associated with cases of community-acquired pneumonia. Because of the morphological peculiarity of M. pneumoniae, which leads to an increased resistance to antibiotics, studies that prospectively investigate the development of vaccines and drug targets appear to be one of the best ways forward. Hence, in this paper, bioinformatics tools were used for vaccine and pharmacological prediction. We conducted comparative genomic analysis on the genomes of 88 M. pneumoniae strains, as opposed to a reverse vaccinology analysis, in relation to the capacity of M. pneumoniae proteins to bind to the major histocompatibility complex, revealing seven targets with immunogenic potential. Predictive cytoplasmic proteins were tested as potential drug targets by studying their structures in relation to other proteins, metabolic pathways and molecular anchorage, which identified five possible drug targets. These findings are a valuable addition to the development of vaccines and the selection of new in vivo drug targets that may contribute to further elucidating the molecular basis of M. pneumoniae-host interactions.