Distinct immunological signatures discriminate severe COVID-19 from non-SARS-CoV-2-driven critical pneumonia.

Immune profiling of COVID-19 patients has identified numerous alterations in both innate and adaptive immunity. However, whether those changes are specific to SARS-CoV-2 or driven by a general inflammatory response shared across severely ill pneumonia patients remains unknown. Here, we compared the immune profile of severe COVID-19 with non-SARS-CoV-2 pneumonia ICU patients using longitudinal, high-dimensional single-cell spectral cytometry and algorithm-guided analysis. COVID-19 and non-SARS-CoV-2 pneumonia both showed increased emergency myelopoiesis and displayed features of adaptive immune paralysis. However, pathological immune signatures suggestive of T cell exhaustion were exclusive to COVID-19. The integration of single-cell profiling with a predicted binding capacity of SARS-CoV-2 peptides to the patients' HLA profile further linked the COVID-19 immunopathology to impaired virus recognition. Toward clinical translation, circulating NKT cell frequency was identified as a predictive biomarker for patient outcome. Our comparative immune map serves to delineate treatment strategies to interfere with the immunopathologic cascade exclusive to severe COVID-19.

Padlock Probe-Based Targeted In Situ Sequencing: Overview of Methods and Applications.

Elucidating spatiotemporal changes in gene expression has been an essential goal in studies of health, development, and disease. In the emerging field of spatially resolved transcriptomics, gene expression profiles are acquired with the tissue architecture maintained, sometimes at cellular resolution. This has allowed for the development of spatial cell atlases, studies of cell-cell interactions, and in situ cell typing. In this review, we focus on padlock probe-based in situ sequencing, which is a targeted spatially resolved transcriptomic method. We summarize recent methodological and computational tool developments and discuss key applications. We also discuss compatibility with other methods and integration with multiomic platforms for future applications.

SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition.

Cluster analysis, a pivotal step in single-cell sequencing data analysis, presents substantial opportunities to effectively unveil the molecular mechanisms underlying cellular heterogeneity and intercellular phenotypic variations. However, the inherent imperfections arise as different clustering algorithms yield diverse estimates of cluster numbers and cluster assignments. This study introduces Single Cell Consistent Clustering based on Spectral Matrix Decomposition (SCSMD), a comprehensive clustering approach that integrates the strengths of multiple methods to determine the optimal clustering scheme. Testing the performance of SCSMD across different distances and employing the bespoke evaluation metric, the methodological selection undergoes validation to ensure the optimal efficacy of the SCSMD. A consistent clustering test is conducted on 15 authentic scRNA-seq datasets. The application of SCSMD to human embryonic stem cell scRNA-seq data successfully identifies known cell types and delineates their developmental trajectories. Similarly, when applied to glioblastoma cells, SCSMD accurately detects pre-existing cell types and provides finer sub-division within one of the original clusters. The results affirm the robust performance of our SCSMD method in terms of both the number of clusters and cluster assignments. Moreover, we have broadened the application scope of SCSMD to encompass larger datasets, thereby furnishing additional evidence of its superiority. The findings suggest that SCSMD is poised for application to additional scRNA-seq datasets and for further downstream analyses.

Diagnosis of Seronegative and Ultrashort Celiac Disease.

In its conventional form, celiac disease (CeD) is characterized by both positive serology and flat villi in the duodenum, and is well known by gastroenterologists and general practitioners. The aim of this review was to shed light on 2 neglected and not yet well-defined celiac phenotypes, that is, seronegative and ultrashort CeD. Seronegative CeD can be suspected in the presence of flat villi, positive HLA-DQ2 and/or HLA-DQ8, and the absence of CeD antibodies. After ruling out other seronegative enteropathies, the diagnosis can be confirmed by both clinical and histologic improvements after 1 year of a gluten-free diet. Ultrashort CeD is characterized by the finding of flat villi in the duodenal bulb in the absence of mucosal damage in the distal duodenum and with serologic positivity. Data on the prevalence, clinical manifestations, histologic lesions, genetic features, and outcome of seronegative and ultrashort CeD are inconclusive due to the few studies available and the small number of patients diagnosed. Some additional diagnostic tools have been developed recently, such as assessing intestinal transglutaminase 2 deposits, flow cytometry technique, microRNA detection, or proteomic analysis, and they seem to be useful in the identification of complex cases. Further cooperative studies are highly desirable to improve the knowledge of these 2 still-obscure variants of CeD.

GOWDL: gene ontology-driven wide and deep learning model for cell typing of scRNA-seq data.

Single-cell RNA-sequencing (scRNA-seq) allows for obtaining genomic and transcriptomic profiles of individual cells. That data make it possible to characterize tissues at the cell level. In this context, one of the main analyses exploiting scRNA-seq data is identifying the cell types within tissue to estimate the quantitative composition of cell populations. Due to the massive amount of available scRNA-seq data, automatic classification approaches for cell typing, based on the most recent deep learning technology, are needed. Here, we present the gene ontology-driven wide and deep learning (GOWDL) model for classifying cell types in several tissues. GOWDL implements a hybrid architecture that considers the functional annotations found in Gene Ontology and the marker genes typical of specific cell types. We performed cross-validation and independent external testing, comparing our algorithm with 12 other state-of-the-art predictors. Classification scores demonstrated that GOWDL reached the best results over five different tissues, except for recall, where we got about 92% versus 97% of the best tool. Finally, we presented a case study on classifying immune cell populations in breast cancer using a hierarchical approach based on GOWDL.

Learning single-cell chromatin accessibility profiles using meta-analytic marker genes.

MOTIVATION: Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a valuable resource to learn cis-regulatory elements such as cell-type specific enhancers and transcription factor binding sites. However, cell-type identification of scATAC-seq data is known to be challenging due to the heterogeneity derived from different protocols and the high dropout rate. RESULTS: In this study, we perform a systematic comparison of seven scATAC-seq datasets of mouse brain to benchmark the efficacy of neuronal cell-type annotation from gene sets. We find that redundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation across the data collected from different studies. Interestingly, simple aggregation of such marker genes achieves performance comparable or higher than that of machine-learning classifiers, suggesting its potential for downstream applications. Based on our results, we reannotated all scATAC-seq data for detailed cell types using robust marker genes. Their meta scATAC-seq profiles are publicly available at https://gillisweb.cshl.edu/Meta_scATAC. Furthermore, we trained a deep neural network to predict chromatin accessibility from only DNA sequence and identified key motifs enriched for each neuronal subtype. Those predicted profiles are visualized together in our database as a valuable resource to explore cell-type specific epigenetic regulation in a sequence-dependent and -independent manner.

Systems biology approach to functionally assess the Clostridioides difficile pangenome reveals genetic diversity with discriminatory power.

Combatting Clostridioides difficile infections, a dominant cause of hospital-associated infections with incidence and resulting deaths increasing worldwide, is complicated by the frequent emergence of new virulent strains. Here, we employ whole-genome sequencing, high-throughput phenotypic screenings, and genome-scale models of metabolism to evaluate the genetic diversity of 451 strains of C. difficile. Constructing the C. difficile pangenome based on this set revealed 9,924 distinct gene clusters, of which 2,899 (29%) are defined as core, 2,968 (30%) are defined as unique, and the remaining 4,057 (41%) are defined as accessory. We develop a strain typing method, sequence typing by accessory genome (STAG), that identifies 176 genetically distinct groups of strains and allows for explicit interrogation of accessory gene content. Thirty-five strains representative of the overall set were experimentally profiled on 95 different nutrient sources, revealing 26 distinct growth profiles and unique nutrient preferences; 451 strain-specific genome scale models of metabolism were constructed, allowing us to computationally probe phenotypic diversity in 28,864 unique conditions. The models create a mechanistic link between the observed phenotypes and strain-specific genetic differences and exhibit an ability to correctly predict growth in 76% of measured cases. The typing and model predictions are used to identify and contextualize discriminating genetic features and phenotypes that may contribute to the emergence of new problematic strains.

Three-Dimensional Visualization of Breast Cancer Pathology Evolution in Clinical Patient Tissues with NIR-II Imaging.

Breast cancer (BC) is the most common tumor worldwide and requires crucial molecular typing for treatment and prognosis assessment. Currently, approaches like pathological staining, immunohistochemistry (IHC), and immunofluorescence (IF) face limitations due to the low signal-to-background ratio (SBR) and high tumor heterogeneity, resulting in a high misdiagnosis rate. Fluorescent assay in the second near-infrared region (NIR-II, 1000-1700 nm) exhibits ultrahigh SBR owing to diminished scattering and tissue autofluorescence. Here, we present a NIR-II strategy for accurate BC molecular typing and three-dimensional (3D) visualization based on the atomically precise fluorescent Au24Pr1 clusters. Single-atom Pr doping results in 3.9-fold fluorescence enhancement and long-term photostability. The Au24Pr1 clusters possess high fluorescence centered at ∼1100 nm and the SBR on pathological section diagnosis was 4 times higher than that of NIR-I imaging. This enables high spatial resolution 3D visualization of biopsy specimens, which can surmount tissue heterogeneity for clinical diagnosis of BC.

Molecular methods enhance the detection of pyoderma-related Streptococcus pyogenes and emm-type distribution in children.

BACKGROUND: Streptococcus pyogenes-related skin infections are increasingly implicated in the development of rheumatic heart disease (RHD) in lower-resourced settings, where they are often associated with scabies. The true prevalence of S. pyogenes-related pyoderma may be underestimated by bacterial culture. METHODS: A multiplex qPCR for S. pyogenes, Staphylococcus aureus and Sarcoptes scabiei was applied to 250 pyoderma swabs from a cross-sectional study of children <5 years in The Gambia. Direct PCR-based emm-typing was used to supplement previous whole genome sequencing (WGS) of cultured isolates. RESULTS: Pyoderma lesions with S. pyogenes increased from 51% (127/250) using culture to 80% (199/250) with qPCR. Compared to qPCR, the sensitivity of culture was 95.4% for S. pyogenes (95% CI 77.2-99.9) in samples with S. pyogenes alone (22/250, 9%), but 59.9% (95% CI 52.3-67.2) for samples with S. aureus co-infection (177/250, 71%). Direct PCR-based emm-typing was successful in 50% (46/92) of cases, identifying 27 emm-types, including six not identified by WGS (total 52 emm-types). CONCLUSIONS: Bacterial culture significantly underestimates the burden of S. pyogenes in pyoderma, particularly when co-infected with S. aureus. Molecular methods should be used to enhance the detection of S. pyogenes in surveillance studies and clinical trials of preventative measures in RHD-endemic settings.

A novel qPCR-based technique for identifying avian sex: An illustration within embryonic craniofacial bone.

Sex is a biological variable important to consider in all biomedical experiments. However, doing so in avian embryos can be challenging as sex can be morphologically indistinguishable. Unlike humans, female birds are the heterogametic sex with Z and W sex chromosomes. The female-specific W chromosome has previously been identified in chick using a species-specific polymerase chain reaction (PCR) technique. We developed a novel reverse transcription quantitative PCR (RT-qPCR) technique that amplifies the W chromosome gene histidine triad nucleotide-binding protein W (HINTW) in chick, quail, and duck. Accuracy of the HINTW RT-qPCR primer set was confirmed in all three species using species-specific PCR, including a novel quail-specific HINTW PCR primer set. Bone development-related gene expression was then analyzed by sex in embryonic lower jaws of duck and quail, as adult duck beak size is known to be sexually dimorphic while quail beak size is not. Trends toward sex differences were found in duck gene expression but not in quail, as expected. With these novel RT-qPCR and PCR embryo sexing methods, sex of chick, quail, and duck embryos can now be assessed by either/both RNA and DNA, which facilitates analysis of sex as a biological variable in studies using these model organisms.

CAraCAl: CAMML with the integration of chromatin accessibility.

BACKGROUND: A vital step in analyzing single-cell data is ascertaining which cell types are present in a dataset, and at what abundance. In many diseases, the proportions of varying cell types can have important implications for health and prognosis. Most approaches for cell type annotation have centered around cell typing for single-cell RNA-sequencing (scRNA-seq) and have had promising success. However, reliable methods are lacking for many other single-cell modalities such as single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq), which quantifies the extent to which genes of interest in each cell are epigenetically "open" for expression. RESULTS: To leverage the informative potential of scATAC-seq data, we developed CAMML with the integration of chromatin accessibility (CAraCAl), a bioinformatic method that performs cell typing on scATAC-seq data. CAraCAl performs cell typing by scoring each cell for its enrichment of cell type-specific gene sets. These gene sets are composed of the most upregulated or downregulated genes present in each cell type according to projected gene activity. CONCLUSIONS: We found that CAraCAl does not improve performance beyond CAMML when scRNA-seq is present, but if only scATAC-seq is available, CAraCAl performs cell typing relatively successfully. As such, we also discuss best practices for cell typing and the strengths and weaknesses of various cell annotation options.

refMLST: reference-based multilocus sequence typing enables universal bacterial typing.

BACKGROUND: Commonly used approaches for genomic investigation of bacterial outbreaks, including SNP and gene-by-gene approaches, are limited by the requirement for background genomes and curated allele schemes, respectively. As a result, they only work on a select subset of known organisms, and fail on novel or less studied pathogens. We introduce refMLST, a gene-by-gene approach using the reference genome of a bacterium to form a scalable, reproducible and robust method to perform outbreak investigation. RESULTS: When applied to multiple outbreak causing bacteria including 1263 Salmonella enterica, 331 Yersinia enterocolitica and 6526 Campylobacter jejuni genomes, refMLST enabled consistent clustering, improved resolution, and faster processing in comparison to commonly used tools like chewieSnake. CONCLUSIONS: refMLST is a novel multilocus sequence typing approach that is applicable to any bacterial species with a public reference genome, does not require a curated scheme, and automatically accounts for genetic recombination. AVAILABILITY AND IMPLEMENTATION: refMLST is freely available for academic use at https://bugseq.com/academic .

Orthanq: transparent and uncertainty-aware haplotype quantification with application in HLA-typing.

BACKGROUND: Identification of human leukocyte antigen (HLA) types from DNA-sequenced human samples is important in organ transplantation and cancer immunotherapy and remains a challenging task considering sequence homology and extreme polymorphism of HLA genes. RESULTS: We present Orthanq, a novel statistical model and corresponding application for transparent and uncertainty-aware quantification of haplotypes. We utilize our approach to perform HLA typing while, for the first time, reporting uncertainty of predictions and transparently observing mutations beyond reported HLA types. Using 99 gold standard samples from 1000 Genomes, Illumina Platinum Genomes and Genome In a Bottle projects, we show that Orthanq can provide overall superior accuracy and shorter runtimes than state-of-the-art HLA typers. CONCLUSIONS: Orthanq is the first approach that allows to directly utilize existing pangenome alignments and type all HLA loci. Moreover, it can be generalized for usages beyond HLA typing, e.g. for virus lineage quantification. Orthanq is available under https://orthanq.github.io .

A Community-Curated DokuWiki Resource on Diagnostics, Diversity, Pathogenicity, and Genetic Control of Xanthomonads.

Xanthomonads, including Xanthomonas and Xylella species, constitute a large and significant group of economically and ecologically important plant pathogens. Up-to-date knowledge of these pathogens and their hosts is essential for the development of suitable control measures. Traditional review articles or book chapters have inherent limitations, including static content and rapid obsolescence. To address these challenges, we have developed a Web-based knowledge platform dedicated to xanthomonads, inspired by the concept of living systematic reviews. This platform offers a dynamic resource that encompasses bacterial virulence factors, plant resistance genes, and tools for diagnostics and genetic diversity studies. Our goal is to facilitate access for newcomers to the field, provide continuing education opportunities for students, assist plant protection services with diagnostics, provide valuable information to breeders on sources of resistance and breeding targets, and offer comprehensive expert knowledge to other stakeholders interested in plant-pathogenic xanthomonads. This resource is available for queries and updates at https://euroxanth.ipn.pt. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Antimicrobial resistance and heterogeneity of Neisseria gonorrhoeae isolated from patients attending sexually transmitted infection clinics in Lusaka, Zambia.

BACKGROUND: Antimicrobial resistance (AMR) of Neisseria gonorrhoeae is a threat to public health as strains have developed resistance to antimicrobials available for the treatment of gonorrhea. Whole genome sequencing (WGS) can detect and predict antimicrobial resistance to enhance the control and prevention of gonorrhea. Data on the molecular epidemiology of N. gonorrhoeae is sparse in Zambia. This study aimed to determine the genetic diversity of N. gonorrhoeae isolated from patients attending sexually transmitted infection (STI) clinics in Lusaka, Zambia. METHODS: A cross-sectional study that sequenced 38 N. gonorrhoeae isolated from 122 patients with gonorrhea from 2019 to 2020 was conducted. The AMR profiles were determined by the E-test, and the DNA was extracted using the NucliSens easyMaG magnetic device. Whole genome sequencing was performed on the Illumina NextSeq550 platform. The Bacterial analysis pipeline (BAP) that is readily available at: https://cge.cbs.dtu.dk/services/CGEpipeline-1.1 was used for the identification of the species, assembling the genome, multi-locus sequence typing (MLST), detection of plasmids and AMR genes. Phylogeny by single nucleotide polymorphisms (SNPs) was determined with the CCphylo dataset. RESULTS: The most frequent STs with 18.4% of isolates each were ST7363, ST1921 and ST1582, followed by ST1583 (13%), novel ST17026 (7.9%), ST1588 (7.9%), ST1596 (5.3%), ST11181 (5.3%), ST11750 (2.6/%) and ST11241 (2.6%) among the 38 genotyped isolates. The blaTeM-1B and tetM (55%) was the most prevalent combination of AMR genes, followed by blaTeM-1B (18.4%), tetM (15.8%), and the combination of blaTeM-1B, ermT, and tetL was 2.6% of the isolates. The AMR phenotypes were predicted in ciprofloxacin, penicillin, tetracycline, azithromycin, and cefixime. The combination of mutations 23.7% was gryA (S91F), parC (E91G), ponA (L421) and rpsJ (V57M), followed by 18.4% in gyrA (S91F), ponA (L421P), rpsJ (V57M), and 18.4% in gyrA (D95G, S91F), ponA (L421P), and rpsJ (V57M). The combinations in gyrA (D95G, S91F) and rpsJ (V57M), and gyrA (D95G, S91F), parC (E91F), ponA (L421P) and rpsJ (V57M) were 13.2% each of the isolates. Plasmid TEM-1 (84.2%), tetM (15.8%), and gonococcal genetic island (GGI) was detected in all isolates. CONCLUSION: This study revealed remarkable heterogeneity of N. gonorrhoeae with blaTEM-1, tetM, ponA, gyrA, and parC genes associated with high resistance to penicillin, tetracycline, and ciprofloxacin demanding revision of the standard treatment guidelines and improved antimicrobial stewardship in Zambia.

Clustering of Polymorphic Membrane Protein E Clade in Chlamydia trachomatis Lineages from Men Who Have Sex with Men.

Several Chlamydia trachomatis lineages identified through outer membrane protein A genotyping or multilocus sequence typing have been circulating worldwide among men who have sex with men. In a study in Tokyo, Japan, we demonstrate that such lineages commonly belong to a specific polymorphic membrane protein E clade across genotypes.

Newly Recognized Spotted Fever Group Rickettsia as Cause of Severe Rocky Mountain Spotted Fever-Like Illness, Northern California, USA.

The incidence of spotted fever group (SFG) rickettsioses in the United States has tripled since 2010. Rocky Mountain spotted fever, the most severe SFG rickettsiosis, is caused by Rickettsia rickettsii. The lack of species-specific confirmatory testing obfuscates the relative contribution of R. rickettsii and other SFG Rickettsia to this increase. We report a newly recognized rickettsial pathogen, Rickettsia sp. CA6269, as the cause of severe Rocky Mountain spotted fever-like illness in 2 case-patients residing in northern California. Multilocus sequence typing supported the recognition of this pathogen as a novel Rickettsia genotype most closely related to R. rickettsii. Cross-reactivity observed for an established molecular diagnostic test indicated that Rickettsia sp. CA6269 might be misidentified as R. rickettsii. We developed a Rickettsia sp. CA6269-specific real-time PCR to help resolve this diagnostic challenge and better characterize the spectrum of clinical disease and ecologic epidemiology of this pathogen.

Environmental Hot Spots and Resistance-Associated Application Practices for Azole-Resistant Aspergillus fumigatus, Denmark, 2020-2023.

Azole-resistant Aspergillus fumigatus (ARAf) fungi have been found inconsistently in the environment in Denmark since 2010. During 2018-2020, nationwide surveillance of clinical A. fumigatus fungi reported environmental TR34/L98H or TR46/Y121F/T289A resistance mutations in 3.6% of isolates, prompting environmental sampling for ARAf and azole fungicides and investigation for selection of ARAf in field and microcosmos experiments. ARAf was ubiquitous (20% of 366 samples; 16% TR34/L98H- and 4% TR46/Y121F/T289A-related mechanisms), constituting 4.2% of 4,538 A. fumigatus isolates. The highest proportions were in flower- and compost-related samples but were not correlated with azole-fungicide application concentrations. Genotyping showed clustering of tandem repeat-related ARAf and overlaps with clinical isolates in Denmark. A. fumigatus fungi grew poorly in the field experiment with no postapplication change in ARAf proportions. However, in microcosmos experiments, a sustained complete (tebuconazole) or partial (prothioconazole) inhibition against wild-type A. fumigatus but not ARAf indicated that, under some conditions, azole fungicides may favor growth of ARAf in soil.

SARS-CoV-2 and Other Coronaviruses in Rats, Berlin, Germany, 2023.

We tested 130 rats captured in Berlin for coronaviruses. SARS-CoV-2 antibodies were detected in 1 rat, but all animals were negative by reverse transcription PCR, suggesting SARS-CoV-2 was not circulating in the rat population. However, alphacoronaviruses were found. Monitoring rodent populations helps to determine coronavirus occurrence, transmission, and zoonotic potential.

Macrolide-Resistant Mycoplasma pneumoniae Infections among Children before and during COVID-19 Pandemic, Taiwan, 2017-2023.

Before the COVID-19 pandemic, Mycoplasma pneumoniae infections emerged during spring to summer yearly in Taiwan, but infections were few during the pandemic. M. pneumoniae macrolide resistance soared to 85.7% in 2020 but declined to 0% during 2022-2023. Continued molecular surveillance is necessary to monitor trends in macrolide-resistant M. pneumoniae.