Molecular Typing Methods Research Articles

Molecular epidemiology and antimicrobial resistance patterns of carbapenem-resistant Acinetobacter baumannii isolates from patients admitted at ICUs of a teaching hospital in Zunyi, China.

Carbapenem-resistant Acinetobacter baumannii (CRAB) has emerged as a predominant strain of healthcare-associated infections worldwide, particularly in intensive care units (ICUs). Therefore, it is imperative to study the molecular epidemiology of CRAB in the ICUs using multiple molecular typing methods to lay the foundation for the development of infection prevention and control strategies. This study aimed to determine the antimicrobial susceptibility profile, the molecular epidemiology and conduct homology analysis on CRAB strains isolated from ICUs. The sensitivity to various antimicrobials was determined using the minimum inhibitory concentration (MIC) method, Kirby-Bauer disk diffusion (KBDD), and E-test assays. Resistance genes were identified by polymerase chain reaction (PCR). Molecular typing was performed using multilocus sequence typing (MLST) and multiple-locus variable-number tandem repeat analysis (MLVA). Among the 79 isolates collected, they exhibited high resistance tovarious antimicrobials but showed low resistance to levofloxacin, trimethoprim-sulfamethoxazole, and tetracyclines. Notably, all isolates of A. baumannii were identified as multidrug-resistant A. baumannii (MDR-AB). The bla OXA-51-like, adeJ, and adeG genes were all detected, while the detection rates of bla OXA-23-like (97.5%), adeB (93.67%), bla ADC (93.67%), qacEΔ1-sul1 (84.81%) were higher; most of the Ambler class A and class B genes were not detected. MLST analysis on the 79 isolates identified five sequence types (STs), which belonged to group 3 clonal complexes 369. ST1145Ox was the most frequently observed ST with a count of 56 out of 79 isolates (70.89%). MLST analysis for non-sensitive tigecycline isolates, which were revealed ST1145Ox and ST1417Ox as well. By using the MLVA assay, the 79 isolates could be grouped into a total of 64 distinct MTs with eleven clusters identified in them. Minimum spanning tree analysis defined seven different MLVA complexes (MCs) labeled MC1 to MC6 along with twenty singletons. The locus MLVA-AB_2396 demonstrated the highest Simpson's diversity index value at 0.829 among all loci tested in this study while also having one of the highest variety of tandem repeat species. The molecular diversity and clonal affinities within the genomes of the CRAB strains were clearly evident, with the identification of ST1144Ox, ST1658Ox, and ST1646Oxqaq representing novel findings.

Genotypic and antimicrobial susceptibility of Streptococcus agalactiae causing bovine mastitis in the central region of Thailand.

Streptococcus agalactiae is a highly contagious pathogen that causes bovine mastitis, leading to significant economic losses. This study aimed to (1) identify and characterize S. agalactiae strains responsible for bovine mastitis by examining their phenotypic and genotypic characteristics in Thai dairy-intensive farming areas and (2) determine their susceptibility profiles to antimicrobial agents. In total, 100 S. agalactiae isolates obtained from clinical and subclinical mastitis cases from 13 dairy herds located in the central region of Thailand were examined. To confirm the identity of the bacterial pathogens, conventional microbiological procedures recommended by the National Mastitis Council (NMC) and the VITEK® 2 system were employed. All 100 isolates were successfully identified as S. agalactiae using the NMC procedure, whereas 94 isolates were identified as S. agalactiae using the VITEK® 2 system. Finally, the S. agalactiae-specific gene dlt S was identified in all the examined isolates using polymerase chain reaction. Capsular polysaccharide (CPS) typing revealed that all strains belonged to CPS type Ia. Multilocus sequence typing identified 33 selected isolates as sequence type 103. Random amplified polymorphic DNA (RAPD) typing yielded 43 RAPD types, with 6 RAPD clusters identified. These results demonstrated a high level of genetic diversity among S. agalactiae within the studied herds. RAPD analysis suggested that specific S. agalactiae strains could persist in dairy farms for 2-12 months. Furthermore, antimicrobial susceptibility testing was performed using the broth microdilution method. Most strains demonstrated susceptibility to ampicillin, penicillin, penicillin/novobiocin, cephalothin, oxacillin, ceftiofur, and erythromycin. This study revealed the phenotypic and genotypic characteristics of S. agalactiae isolates responsible for bovine mastitis in the central region of Thailand. The rapid identification of S. agalactiae and application of molecular typing methods can provide valuable epidemiological information regarding S. agalactiae causing mastitis in dairy farms. The antimicrobial susceptibility of S. agalactiae indicates that antimicrobial treatment for control and eradication could be a successful protocol. Our findings revealed that a single clonal strain of S. agalactiae affected the 13 studied farms. Further research is needed to explore the feasibility of vaccine development and application.

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

BackgroundProstate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy.MethodsAn integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms.ResultsWe identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments.ConclusionsThe three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.

The Enterotoxin Gene Profiles and Enterotoxin Production of Staphylococcus aureus Strains Isolated from Artisanal Cheeses in Belgium.

A Staphyloccoccus aureus is one of the leading causes of food poisoning outbreaks (FPOs) worldwide. Staphylococcal food poisoning (SFP) is induced by the ingestion of food containing sufficient levels of staphylococcal enterotoxins (SEs). Currently, 33 SEs and SE-like toxins (SEls) have been described in the literature, but only five named "classical" enterotoxins are commonly investigated in FPOs due to lack of specific routine analytical techniques. The aims of this study were to (i) establish the genetic profile of strains in a variety of artisanal cheeses (n = 30) in Belgium, (ii) analyze the expression of the SE(l)s by these strains and (iii) compare the output derived from the different analytical tools. Forty-nine isolates of S. aureus were isolated from ten Belgian artisanal cheeses and were analyzed via microbiological, immunological, liquid chromatography mass spectrometry, molecular typing and genetic methods. The results indicated that classical SEs were not the dominant SEs in the Belgian artisanal cheeses that were analyzed in this study, and that all S. aureus isolates harbored at least one gene encoding a new SE(l). Among the new SE(l)s genes found, some of them code for enterotoxins with demonstrated emetic activity and ecg-enterotoxins. It is worth noting that the involvement of some of these new SEs has been demonstrated in SFP outbreaks. Thus, this study highlighted the importance of the development of specific techniques for the proper investigation of SFP outbreaks.

Comparative study on three molecular typing methods of Vibrio parahaemolyticus

To evaluate the correlation among the three molecular typing method of pulsed field gel electrophoresis(PFGE), repetitive extragenic palindromic(REP)-PCR and en-terobacterial repetitive intergenic consensus(ERIC)-PCR, and to explore the genetic relationship among strains, and to further understand the distribution and epidemic trend of Vibrio parahaemolyticus in Liaoning Province by combining Serotype analysis. Serum typing, PFGE, REP-PCR, and ERIC-PCR molecular typing and cluster analysis were performed on 150 VP isolates from Liaoning Province in 2018. 118 isolates could be divided into 14 Serotype, and 32 isolates could not be classified. The main serotypes were O3, O1 and O2. The resolution(DI) of PFGE is 0.969, the resolution(DI) of REP-PCR is 0.948, and the resolution(DI) of ERIC-PCR is 0.927. The Serotype O3 group strains are highly similar to the molecular types of O1 group strains. In 2018, the epidemic Serotype of clinical VP isolates in Liaoning Province is still O3: K6, and the epidemic serotype of food VP isolates is still O2. The result of PFGE, REP-PCR, and ERIC-PCR typing method are consistent, and the resolution and reproducibility of PFGE typing method are superior to the other two method. The Serotype O3 group is closely related to O1 group.

Core-genome multilocus sequence typing and core-SNP analysis of Clostridium neonatale strains isolated in different spatio-temporal settings.

Clostridium neonatale was described as a new species within the Clostridium genus cluster I sensu stricto. It was recovered from the gut microbiota of infants and has been associated with necrotizing enterocolitis (NEC), a severe gastrointestinal disease affecting preterm neonates. In the absence of molecular typing methods, we developed a core (cg)-genome multilocus sequence typing (MLST) scheme based on 48 newly sequenced and 12 publicly available genomes of C. neonatale. Using the ChewBBACA algorithm, a stable MLST scheme consisting of 2,350 target genes (with genomes having ≥95% cgMLST targets) is proposed. The strains are distributed among five clades, and while some are clonality related within clades, the C. neonatale strain distribution is independent of geographic or temporal clustering. When considering strains isolated from patients with and without NEC, there were no observable differences in clustering. When compared to a core-single nucleotide polymorphism (SNP) analysis approach (31,248 positions), we showed that both cgMLST and cgSNP have comparable genetic discrimination of strains. In this study, we validated the use of cgMLST and cgSNP-based typing methods for the genetic comparison of clinical isolates of C. neonatale, which will allow for future surveillance and epidemiological clinical investigations of this potential opportunistic pathogen.IMPORTANCEClostridium neonatale has been isolated from the fecal samples of asymptomatic neonates and cases of necrotizing enterocolitis (NEC). Taking advantage of a large collection of independent strains isolated from different spatio-temporal settings, we developed and established a cgMLST scheme for the molecular typing of C. neonatale. Both the cgMLST and cgSNP methods demonstrate comparable discrimination power. Results indicate geographic- and temporal- independent clustering of C. neonatale NEC-associated strains. No specific cgMLST clade of C. neonatale was genetically associated with NEC.

Application of Next-Generation Sequencing to Enterobacter Hormaechei Subspecies Analysis during a Neonatal Intensive Care Unit Outbreak.

The Enterobacter cloacae complex (ECC) species are potential neonatal pathogens, and ECC strains are among the most commonly encountered Enterobacter spp. associated with nosocomial bloodstream infections. Outbreaks caused by ECC can lead to significant morbidity and mortality in susceptible neonates. At the molecular level, ECC exhibits genomic heterogeneity, with six closely related species and subspecies. Genetic variability poses a challenge in accurately identifying outbreaks by determining the clonality of ECC isolates. This difficulty is further compounded by the limitations of the commonly used molecular typing methods, such as pulsed field gel electrophoresis, which do not provide reliable accuracy in distinguishing between ECC strains and can lead to incorrect conclusions. Next-generation sequencing (NGS) offers superior resolution in determining strain relatedness. Therefore, we investigated the clinical pertinence of incorporating NGS into existing bundle measures to enhance patient management during an outbreak of ECC in a level-3 neonatal intensive care unit (NICU) in Germany. As the standard of care, all neonates on the NICU received weekly microbiological swabs (nasopharyngeal and rectal) and analysis of endotracheal secretion, where feasible. During the 2.5-month outbreak, colonisation with ECC was detected in n = 10 neonates. The phylogenetic relationship and potential antimicrobial resistance genes as well as mobile genetic elements were identified via bacterial whole-genome sequencing (WGS) using Illumina MiSeq followed by in silico data analysis. Although all ECC isolates exhibited almost identical antimicrobial susceptibility patterns, the WGS data revealed the involvement of four different ECC clones. The isolates could be characterised as Enterobacter hormaechei subspecies steigerwaltii (n = 6, clonal), subsp. hoffmannii (n = 3, two clones) and subsp. oharae (n = 1). Despite the collection of environmental samples, no source of this diffuse outbreak could be identified. A new standardised operating procedure was implemented to enhance the management of neonates colonised with MRGN. This collaborative approach involved both parents and medical professionals and successfully prevented further transmission of ECC. Initially, it was believed that the NICU outbreak was caused by a single ECC clone due to the similarity in antibiotic resistance. However, our findings show that antibiotic susceptibility patterns can be misleading in investigating outbreaks of multi-drug-resistant ECC. In contrast, bacterial WGS accurately identified ECC at the clonal level, which significantly helped to delineate the nature of the observed outbreak.

A core-genome multilocus sequence typing scheme for the detection of genetically related Streptococcus pyogenes clusters.

The recently observed increase in invasive Streptococcus pyogenes infections causes concern in Europe. However, conventional molecular typing methods lack discriminatory power to aid investigations of outbreaks caused by S. pyogenes. Therefore, there is an urgent need for high-resolution molecular typing methods to assess genetic relatedness between S. pyogenes isolates. In the current study, we aimed to develop a novel high-resolution core-genome multilocus sequence typing (cgMLST) scheme for S. pyogenes and compared its discriminatory power to conventional molecular typing methods. The cgMLST scheme was designed with the commercial Ridom SeqSphere+ software package. To define a cluster threshold, the scheme was evaluated using publicly available data from nine defined S. pyogenes outbreaks in the United Kingdom. The cgMLST scheme was then applied to 23 isolates from a suspected S. pyogenes outbreak and 117 S. pyogenes surveillance isolates both from the Netherlands. MLST and emm-typing results were used for comparison to cgMLST results. The allelic differences between isolates from defined outbreaks ranged between 6 and 31 for isolates with the same emm-type, resulting in a proposed cluster threshold of <5 allelic differences out of 1,095 target loci. Seven out of twenty-three (30%) isolates from the suspected outbreak had an allelic difference of <2, thereby identifying a potential cluster that could not be linked to other isolates. The proposed cgMLST scheme shows a higher discriminatory ability when compared to conventional typing methods. The rapid and simple analysis workflow allows for extended detection of clusters of potential outbreak isolates and surveillance and may facilitate the sharing of sequencing results between (inter)national laboratories.

Molecular Detection and Typing of Treponema pallidum in Non-Ocular Samples from Patients with Ocular Syphilis

ABSTRACT Introduction Ocular syphilis is a rare but potentially sight-threatening manifestation of infection with the spirochete Treponema pallidum subspecies pallidum. Molecular strain typing of clinical specimens obtained from patients with syphilis can provide useful epidemiological and clinical information. In this study, we assess the utility of non-ocular clinical samples in strain typing for patients with diagnosed ocular syphilis. Methods We collected samples of excess blood, serum, and cerebrospinal fluid (CSF) from 6 patients with ocular syphilis treated in 2013–2016. DNA was extracted, purified, and then analyzed using an enhanced molecular typing method including sequence analysis of tp0548, number of repeats in the arp gene, and restriction fragment length polymorphism of the tpr gene. Results Molecular strain typing based on tp0548 gene sequence analysis revealed two cases of type F and two cases of type G in 3 of 6 (50%) cases with CSF samples, 1 of which was obtained after starting antibiotics. In a patient with 2 distinct episodes, the same tp0548 type (type G) was identified in both episodes using different sample types (CSF, whole blood). Serum samples were available in 6 cases, but none were successfully typed with any of the methods. Amplification of the tpr and arp genes was unsuccessful in all cases. Overall, strain types were identified in 4 of the 7 episodes. Conclusion Treponema pallidum strain types F and G were detected in CSF or whole blood in 4 of 7 episodes in this series. We demonstrate moderate sensitivity of strain typing in ocular syphilis using non-ocular clinical specimens.

Comparison of Molecular and Clinicopathologic-Based Classifications and the Transition of Adjuvant Treatment Mode for Early-Stage Endometrial Cancer

Due to the division in classification strategies based on different molecular and clinicopathologic guidelines, the current emergence of multiple molecular typing methods greatly challenges the traditional classification-guided hierarchical treatment model. The early-stage ECs who underwent a total hysterectomy and comprehensive molecular analyses were analyzed consecutively between May 2021 and December 2022. All enrolled patients were performed with immunohistochemistry for lymph-vascular space invasion (LVSI), p53, and mismatch repair (MMR) proteins, NGS-panel Sanger sequencing for POLE exonuclease domain, and TP53. The Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) classifier and the ESGO/ESTRO/ESP guidelines with and without molecular character were respectively employed to reclassify the enrolled patients. Categorical variables of the risk-group shift were compared by Pearson's χ2 or two-sided Fisher's exact test. A total of 81 early-stage ECs patients were enrolled. Molecular analyses identified four subgroups across the 81 ECs: 9 (11%) POLE mut, 22 (27.1%) MMRd, 38 (46.9%) NSMP, and 12 (14.8%) p53 abn. Compared with ESGO/ESTRO/ESP 2016 classifier, 26 (32.1%) and 23 (28.4%) patients in ESGO/ESTRO/ESP 2020 cohort with and without molecular classification, respectively, were risk-group downshifted (p>0.05). Ten (12.3%) patients were upshifted in ESGO/ESTRO/ESP 2020 molecular classification comparing to clinical classifier. Remarkably, two patients demonstrated discordance between the ProMisE and TCGA classifiers since the different sequences of classification strategies. On the other hand, 48 of 81 patients received adjuvant radiotherapy, and 12 patients received external beam radiation therapy (EBRT). According to the final molecular test, eight of 12 were classified into low and intermediate risk. The treatment of endometrial cancer is in a period of transition from the clinicopathologic-based model to the era of molecular precision. Discordance between different classifiers and overtreatment remain in clinical practice. Therefore, we should be cautious about using molecular typing to guide adjuvant treatment decisions until it is finally validated in prospective trials.

Molecular Typing of Multidrug-Resistant Acinetobacter baumannii Isolates from Clinical Specimens by ERIC-PCR and MLVA.

Acinetobacter baumannii, a Gram-negative and oxidase-negative bacterium, is a major cause of nosocomial infections, leading to high mortality rates in hospitalized patients. The use of 2 prominent molecular typing methods (i.e., enterobacterial repetitive intergenic consensus-polymerase chain reaction [ERIC-PCR] and multiple-locus variable-number tandem repeat [VNTR] analysis [MLVA]) for genotyping A. baumannii isolates has proven to be an effective approach in assessing the clonal relation of these isolates and managing their outbreaks. A total of 100 A. baumannii isolates were collected from immunocompromised patients hospitalized in the intensive care unit (ICU) of a hospital in Zanjan City, Iran. Their antibiotic resistance ability (especially aminoglycoside resistance) was studied by disc diffusion tests. The genetic typing of A. baumannii was studied using ERIC-PCR and MLVA methods. All isolates were resistant to 3 or more antibiotics and regarded as multidrug-resistant (MDR). Additionally, 32% of the isolates were resistant to all antibiotics tested, and 91% were extensively drug-resistant (XDR). The increased rate of aminoglycoside-resistant A. baumannii in ICU patients, with an increased incidence of aminoglycoside-modifying enzymes of aac (6')-Ib, ant (3″)-I, and aph (2″)-Id. ERIC-PCR has likewise shown an increased level of diversity in A. baumannii isolates. According to the ERIC-PCR patterns, isolates were classified as 4 clusters, while according to the MLVA patterns, isolates were classified as 9 distinct clusters. ERIC-PCR and MLVA assays serve as useful genotyping methods to assess the genetic variety or clonal relatedness of A. baumannii isolates.

Spoligotyping of Mycobacterium tuberculosis – Comparing in vitro and in silico approaches

Spoligotyping is one of the molecular typing methods widely used for exploring the genetic variety of Mycobacterium tuberculosis. The aim of this study was to compare the spoligoprofiles of M. tuberculosis clinical isolates, obtained using in vitro and in silico approaches.The study included 230 M. tuberculosis isolates, recovered from Poland and Lithuania between 2018 and 2021. Spoligotyping in vitro was performed with a commercially available kit. Whole genome sequencing (WGS) was done with Illumina NovaSeq 6000 sequencer. Spoligotype International Types (SITs) were assigned according to the SITVIT2 database or using three different in silico tools, and based on WGS data, namely SpoTyping, SpolPred, and lorikeet.Upon in vitro spoligotyping, the isolates produced 65 different spoligotypes. Spoligotypes inferred from the WGS data were congruent with in vitro generated patterns in 81.7% (188/230) for lorikeet and 81.3% (187/230) for SpolPred and SpoTyping. Spacers 18 and 31 produced the highest ratio of discrepant results between in vitro and in silico approaches, with their signals discordantly assigned for 15 (6.5%) and 9 (3.9%) isolates, respectively.All three in silico approaches used were similarly efficient for M. tuberculosis spoligotype prediction. However, only SpoTyping could predict spoligotypes without a need for manual curation. Thus, we consider it as the most accurate tool. Its use is further advocated by the shortest time of analysis. A relatively high (ca. 20%) discordance between in vitro and in silico spoligotyping results was observed. While we discourage comparing conventional spoligotyping with in silico equivalents, we advise the use of the latter, as it improves the accuracy of spoligopatterns, and thus depicts the relatedness between the isolates more reliably.

Development and validation of an RT-qPCR for detection and quantitation of emerging epizootic hemorrhagic disease virus serotype 8 RNA from field samples

Epizootic hemorrhagic disease virus (EHDV) is a Culicoides-transmitted virus circulating in multiple serotypes. It has become a concern in the European Union as a novel strain of the serotype 8 (EHDV-8) of clear Northern African origin, has been recently discovered in symptomatic cattle in Italy (islands of Sardinia and Sicily), Spain, and Portugal. Current molecular typing methods targeting the S2 nucleotide sequences -coding for the outermost protein of the virion VP2- are not able to detect the novel emerging EHDV-8 strain as they enrolled the S2 sequence of the unique EHDV-8 reference strain isolated in Australia in 1982. Thus, in this study, we developed and validated a novel typing assay for the detection and quantitation of the novel EHDV-8 RNA from field samples, including blood of ruminants and insects. This molecular tool will certainly support EHDV-8 surveillance and control.

Molecular diversity of Mycobacterium tuberculosis isolates in Treatment-experienced Patients from Andhra Pradesh, India.

To get a comprehensive idea about the transmission and epidemiology of TB globally and locally, the use of molecular typing methods has become imperative not only for understanding genetic diversity but also the population structure of Mycobacterium tuberculosis complex (MTBC). We aimed to investigate the drug resistance pattern and genetic diversity of MTBC among previously treated patients with sputum smear-positive pulmonary tuberculosis in a South Indian population. 104 patients with sputum smear positivity and who had previously undergone treatment were selected. Drug susceptibility testing, Spoligotyping, MIRU-VNTR, and SNP typing were performed. Mono-resistance to isoniazid 16 (15.38%) was the highest among all drugs. Out of 104 isolates, 24 (23%) isolates were classified as MDR strains. The distributions of most common lineages were: EAI3-Ind-20 (19.23%), EAI5-13 (12.50%), Beijing-12 (11.54%), CAS1-Delhi- 9 (8.65%), and 7 (6.73%) each of T-H37rv, Unknown and Orphan types. MIRU-VNTR-based analysis revealed that there are two major groups: CAS1-Delhi and Beijing groups. Out of 104 isolates, 82 belonged to well-defined lineages and 6 clusters, and the remaining 22 were singletons. SNP analysis showed no mutations associated with five sets of genes in 33 strains. The occurrence of 11.54% Beijing strains in South India is an important finding. High frequency of Isoniazid mono resistance noticed. Spoligotyping along with MIRU-VNTR and SNP typing is the best approach to the identification of strain lineages. No mutation with Antigen85C gene represents, can be used for vaccine candidates.

Analysis of the role of glucose metabolism-related genes in dilated cardiomyopathy based on bioinformatics.

Dilated cardiomyopathy (DCM) is a prevalent condition with diverse etiologies, including viral infection, autoimmune response, and genetic factors. Despite the crucial role of energy metabolism in cardiac function, therapeutic targets for key genes in DCM's energy metabolism remain scarce. Our study employed the GSE79962 and GSE42955 datasets from the Gene Expression Omnibus (GEO) database for myocardial tissue sample collection and target gene identification via differential gene expression screening. Using various R packages, GSEA software, and the STRING database, we conducted data analysis, gene set enrichment, and protein-protein interaction predictions. The least absolute shrinkage and selection operator (LASSO) and Support Vector Machine (SVM) algorithms aided in feature gene selection, while the predictive model's efficiency was evaluated via the receiver operating characteristic (ROC) curve analysis. We used the non-negative matrix factorization (NMF) method for molecular typing and the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm for predicting immune cell infiltration. The DLAT and LDHA genes may regulate the immune microenvironment of DCM by influencing activated dendritic cells, activated mast cells, and M0 macrophages, respectively. The BPGM, DLAT, PGM2, ADH1A, ADH1C, LDHA, and PFKM genes may regulate m6A methylation in DCM by affecting the ZC3H13, ALKBH5, RBMX, HNRNPC, METTL3, and YTHDC1 genes. Further regulatory mechanism analysis suggested that PFKM, DLAT, PKLR, PGM2, LDHA, BPGM, ADH1A, and ADH1C could be involved in the development of cardiomyopathy by regulating the Toll-like receptor signaling pathway. PFKM, DLAT, PKLR, PGM2, LDHA, BPGM, ADH1A, and ADH1C may serve as potential targets for guiding the diagnosis, treatment, and follow-up of DCM.

Polymerase chain reaction-based typing methods and protein profiling analysis of Acinetobacter baumannii isolated from environmental and clinical sources from South India.

Acinetobacter baumannii is an opportunistic pathogen known for causing hospital-acquired infections. The natural habitat includes soil, water, sewage, and drains, but it is also detected in infected individuals' blood, pus, and respiratory pathways. Due to its resilient nature, it is known to be a causative agent for outbreaks. Therefore, it is crucial to understand the genetic similarity between clinical and environmental isolates. The study aimed to find the genetic relationships between clinical and environmental isolates using PCR-based typing methods such as enterobacterial repetitive intergenic consensus sequence PCR (ERIC-PCR), random amplified polymorphic DNA (RAPD), and repetitive extragenic palindromic sequence-based PCR (Rep-PCR). Additionally, outer membrane protein (OMP) and whole cell protein (WCP) profiles were also used. The PCR-based methods, ERIC-PCR and Rep-PCR, showed decreased genetic similarity between clinical and environmental isolates (66% and 58%, respectively). However, RAPD showed relatively higher genetic similarity (91%). The OMP and WCP profiles showed varied banding patterns between the clinical and environmental isolates in the 29-43 kDa region. The PCR-based methods proved to be a reliable and reproducible technique. The OMP and WCP profiles, though not as discriminatory as the molecular typing methods, could help identify the most and least commonly occurring protein bands and thus help in typing clinical and environmental A. baumannii isolates.

Cryptococcosis in Africa: What the data tell us.

Cryptococcosis is a neglected tropical disease and the main cause of fungal-related deaths in HIV-positive persons in Africa. It is an AIDS-defining illness that has almost surpassed tuberculosis (TB) in mortality despite wide coverage with antiretroviral therapy. What is known about the cryptococcosis burden in Africa is from estimations based on data from a few studies on the infection burden and associated complications. Consequently, the projected implications of cryptococcosis in Africa have been based on these estimations. This systematic review is aimed at providing unique and up-to-date data on the burden of cryptococcosis in Africa using published hospital-based research data on cryptococcosis in HIV infected and uninfected persons. The review also focused on providing temporal data on the availability of diagnostic and therapeutic options for cryptococcosis in Africa. From our results, about 40 948 cases of cryptococcosis were reported in Africa from 1969 to 2021, and the highest prevalence of cryptococcosis was from southern Africa. The most isolated species was Cryptococcus neoformans 42.4% (17 710/41 801) and only 1.3% (549/41 801) isolates were C. gattii. C. neoformans (serotype A) VN I 64.5% (918/1522) was the most prevalent serotype in Africa, while C. gattii (serotype C) VG IV was thought to pose a huge danger. However, C. neoformans (serotype A) VN I continued to be the major threat in Africa. Due to the limited availability of molecular typing methods and the widespread use of culture, direct microscopy, and serological techniques for diagnosis, 23 542 isolates were uncharacterised. Amphotericin B and flucytosine combination therapy is highly recommended for treatment of cryptococcal meningitis. However, these drugs are expensive and remain largely unavailable in most African countries. Amphotericin B requires laboratory facilities to monitor for toxicity. Although fluconazole monotherapy is the readily available treatment option for cryptococcosis, drug resistance, and high mortality have been recorded in majority of cases in Africa. The lack of awareness and paucity of published data on cryptococcosis are likely to have contributed to the underestimation of cases in Africa and led to underprioritisation of this important disease.

Development of a method for molecular subtyping &lt;i&gt;Bacillus anthracis&lt;/i&gt; using HRM PCR

Introduction. Bacillus anthracis is the causative agent of anthrax, a pathogen characterized by high genetic monomorphism that complicates differentiation of strains. Thus, molecular methods for pathogen typing require the improvement.&#x0D; The aim of the study. To select marker SNPs for new genetic groups of B. anthracis and to develop a method for their laboratory identification using HRM PCR.&#x0D; Materials and methods. The core genome of 222 strains of B. anthracis from the GenBank database and 66 strains from the collection of pathogenic microorganisms of the Stavropol Anti-Plague Institute was aligned using the parsnp software. A dendrogram based on 7242 core genome SNPs was built in MEGA X software. The strains for validation of the HRM method included representatives of various genetic groups. The HRM PCR reaction was performed using the "Type-it HRM PCR Kit" and "KAPA HRM FAST qPCR Kit" and a Rotor Gene DNA thermocycler with HRM function. Data analysis and visualization were performed using custom scripts in the Python and R development environments.&#x0D; Results and discussion. Marker SNPs for 6 genetic groups have been identified, which make it possible to determine whether strains belong to one of 7 new subclusters. Pairs of primers were selected for the loci containing them, HRM PCR parameters were optimized for discrimination of different alleles of SNP loci, and an analysis scheme was developed.&#x0D; Conclusion. Thus, marker SNPs were selected to determine the genetic subclusters A.Br.CEA, A.Br.STI, A.Br.Tsiankovskii, B.Br.Europe, B.Br.Siberia, B.Br.Asia, B.Br.018, and a new laboratory method was developed for molecular subtyping of B. anthracis using HRM PCR.

Identification of a Specific Biomarker of Acinetobacter baumannii Global Clone 1 by Machine Learning and PCR Related to Metabolic Fitness of ESKAPE Pathogens.

Since the emergence of high-risk clones worldwide, constant investigations have been undertaken to comprehend the molecular basis that led to their prevalent dissemination in nosocomial settings over time. So far, the complex and multifactorial genetic traits of this type of epidemic clones have allowed only the identification of biomarkers with low specificity. A machine learning algorithm was able to recognize unequivocally a biomarker for early and accurate detection of Acinetobacter baumannii global clone 1 (GC1), one of the most disseminated high-risk clones. A support vector machine model identified the U1 sequence with a length of 367 nucleotides that matched a fragment of the moaCB gene, which encodes the molybdenum cofactor biosynthesis C and B proteins. U1 differentiates specifically between A. baumannii GC1 and non-GC1 strains, becoming a suitable biomarker capable of being translated into clinical settings as a molecular typing method for early diagnosis based on PCR as shown here. Since the metabolic pathways of Mo enzymes have been recognized as putative therapeutic targets for ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) pathogens, our findings highlight that machine learning can also be useful in knowledge gaps of high-risk clones and provides noteworthy support to the literature to identify relevant nosocomial biomarkers for other multidrug-resistant high-risk clones. IMPORTANCE A. baumannii GC1 is an important high-risk clone that rapidly develops extreme drug resistance in the nosocomial niche. Furthermore, several strains have been identified worldwide in environmental samples, exacerbating the risk of human interactions. Early diagnosis is mandatory to limit its dissemination and to outline appropriate antibiotic stewardship schedules. A region with a length of 367 bp (U1) within the moaCB gene that is not subjected to lateral genetic transfer or to antibiotic pressures was successfully found by a support vector machine model that predicts A. baumannii GC1 strains. At the same time, research on the group of Mo enzymes proposed this metabolic pathway related to the superbug's metabolism as a potential future drug target site for ESKAPE pathogens due to its central role in bacterial fitness during infection. These findings confirm that machine learning used for the identification of biomarkers of high-risk lineages can also serve to identify putative novel therapeutic target sites.

Evaluation of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Molecular Typing of Acinetobacter baumannii in Comparison with Orthogonal Methods.

Colonization and subsequent health care-associated infection (HCAI) with Acinetobacter baumannii are a concern for vulnerable patient groups within the hospital setting. Outbreaks involving multidrug-resistant strains are associated with increased patient morbidity and mortality and poorer overall outcomes. Reliable molecular typing methods can help to trace transmission routes and manage outbreaks. In addition to methods deployed by reference laboratories, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) may assist by making initial in-house judgments on strain relatedness. However, limited studies on method reproducibility exist for this application. We applied MALDI-TOF MS typing to A. baumannii isolates associated with a nosocomial outbreak and evaluated different methods for data analysis. In addition, we compared MALDI-TOF MS with whole-genome sequencing (WGS) and Fourier transform infrared spectroscopy (FTIR) as orthogonal methods to further explore their resolution for bacterial strain typing. A related subgroup of isolates consistently clustered separately from the main outbreak group by all investigated methods. This finding, combined with epidemiological data from the outbreak, indicates that these methods identified a separate transmission event unrelated to the main outbreak. However, the MALDI-TOF MS upstream approach introduced measurement variability impacting method reproducibility and limiting its reliability as a standalone typing method. Availability of in-house typing methods with well-characterized sources of measurement uncertainty could assist with rapid and dependable confirmation (or denial) of suspected transmission events. This work highlights some of the steps to be improved before such tools can be fully integrated into routine diagnostic service workflows for strain typing. IMPORTANCE Managing the transmission of antimicrobial resistance necessitates reliable methods for tracking outbreaks. We compared the performance of MALDI-TOF MS with orthogonal approaches for strain typing, including WGS and FTIR, for Acinetobacter baumannii isolates correlated with a health care-associated infection (HCAI) event. Combined with epidemiological data, all methods investigated identified a group of isolates that were temporally and spatially linked to the outbreak, yet potentially attributed to a separate transmission event. This may have implications for guiding infection control strategies during an outbreak. However, the technical reproducibility of MALDI-TOF MS needs to be improved for it to be employed as a standalone typing method, as different stages of the experimental workflow introduced bias influencing interpretation of biomarker peak data. Availability of in-house methods for strain typing of bacteria could improve infection control practices following increased reports of outbreaks of antimicrobial-resistant organisms during the COVID-19 pandemic, related to sessional usage of personal protective equipment (PPE).