Set Of Marker Genes Research Articles

Estimating the quality of eukaryotic genomes recovered from metagenomic analysis with EukCC

Microbial eukaryotes constitute a significant fraction of biodiversity and have recently gained more attention, but the recovery of high-quality metagenomic assembled eukaryotic genomes is limited by the current availability of tools. To help address this, we have developed EukCC, a tool for estimating the quality of eukaryotic genomes based on the automated dynamic selection of single copy marker gene sets. We demonstrate that our method outperforms current genome quality estimators, particularly for estimating contamination, and have applied EukCC to datasets derived from two different environments to enable the identification of novel eukaryote genomes, including one from the human skin.

Establishment and Analysis of a Combined Diagnostic Model of Polycystic Ovary Syndrome with Random Forest and Artificial Neural Network.

Polycystic ovary syndrome (PCOS) is one of the most common metabolic and reproductive endocrinopathies. However, few studies have tried to develop a diagnostic model based on gene biomarkers. In this study, we applied a computational method by combining two machine learning algorithms, including random forest (RF) and artificial neural network (ANN), to identify gene biomarkers and construct diagnostic model. We collected gene expression data from Gene Expression Omnibus (GEO) database containing 76 PCOS samples and 57 normal samples; five datasets were utilized, including one dataset for screening differentially expressed genes (DEGs), two training datasets, and two validation datasets. Firstly, based on RF, 12 key genes in 264 DEGs were identified to be vital for classification of PCOS and normal samples. Moreover, the weights of these key genes were calculated using ANN with microarray and RNA-seq training dataset, respectively. Furthermore, the diagnostic models for two types of datasets were developed and named neuralPCOS. Finally, two validation datasets were used to test and compare the performance of neuralPCOS with other two set of marker genes by area under curve (AUC). Our model achieved an AUC of 0.7273 in microarray dataset, and 0.6488 in RNA-seq dataset. To conclude, we uncovered gene biomarkers and developed a novel diagnostic model of PCOS, which would be helpful for diagnosis.

TOX correlates with prognosis, immune infiltration, and T cells exhaustion in lung adenocarcinoma.

BackgroundThymocyte selection‐associated high mobility group box (TOX) plays a crucial role on the development of innate immunity and tumor microenvironment. This study aims to explore the prognostic potential of TOX and comprehensively analyze the correlations between TOX, immune infiltration, and T cells function in diverse cancers particularly lung adenocarcinoma (LUAD).MethodsTIMER was used to analyze TOX expression in different cancers. Potential prognostic value of TOX was evaluated by the PrognoScan, Kaplan‐Meier Plotter, and GEPIA2. The relationships between TOX, immune infiltration, and related gene marker sets were analyzed by TIMER and GEPIA2. Single‐cell RNA‐seq for T cells in LUAD was analyzed to further investigate the correlations between TOX expression and different T cells populations.ResultsTOX downregulates in most of the cancer types and correlates with poor prognosis in LUAD. TOX shows significant impacts on survival of LUAD with early stage, ever‐smoking, or low‐TMB status. Increased TOX expression positively correlates with high immune infiltration levels in most of the immune cells and functional T cells including exhausted T cells. Moreover, multiple key genes of exhausted T cells comprising PD‐1, TIM‐3, TIGHT, and CXCL13 have remarkable interaction with TOX. Specifically, TOX is observed with high enrichment in exhausted CD4+ and CD8+ T cells populations in single‐cell RNA‐seq analysis for LUAD.ConclusionTOX is a prognosis‐related biomarker for multiple cancer types especially LUAD. Increased TOX expression significantly increase immune infiltration levels in most of the immune cells comprising CD8+ T cells, CD4+ T cells, mast cells, and functional T cells. Moreover, we verified that TOX highly correlates with exhausted T cells and is probable a critical regulator promoted T cells exhaustion in LUAD. Detection of TOX expression could help to predict prognosis and regulating TOX expression in exhausted T cells may offer a novel strategy in maximizing immunotherapy efficacy for LUAD.

DCK is a promising prognostic biomarker and correlated with immune infiltrates in hepatocellular carcinoma

BackgroundDeoxycytidine kinase (DCK), an enzyme in the nucleoside biosynthetic pathway, can affect the development of immune cells. However, the relationships between the expression of DCK, patient prognosis, and tumor-infiltrating immune cells (TIICs) in hepatocellular carcinoma (HCC) are still unclear.MethodsThe expression of DCK in HCC was analyzed through the Oncomine and Tumor Immune Estimation Resource (TIMER) databases. The impact of DCK on clinical prognosis was investigated via the Kaplan-Meier plotter and verified in the Gene Expression Profiling Interactive Analysis (GEPIA) databases. The interrelationships between DCK expression and TIICs in HCC were analyzed by the TIMER database. Additionally, the relationship between DCK expression and immune cell gene markers was calculated through TIMER and GEPIA databases.ResultsCompared with the adjacent normal tissues, high expression of DCK was observed in HCC tissues. Also, the higher expression of DCK was correlated to poorer prognosis in HCC patients, and it was associated with decreased survival in those with early stage and grade. Moreover, DCK expression was positively correlated with TIICs, including CD4+ and CD8+ T cells, B cells, monocytes, tumor-associated macrophages (TAMs), M1 and M2 macrophages, neutrophils, natural killer cells, and dendritic cells. Specifically, DCK expression levels were significantly associated with diverse immune gene marker sets, including those of Tregs and exhausted T cells.ConclusionThese findings suggest that DCK expression is correlated with patient outcomes and tumor infiltration cell levels in HCC patients. Additionally, the increased level of DCK was associated with marker genes of Tregs and exhaustion-related inhibitory receptors, suggesting the potential role of DCK in immunosuppression and immune escape. These findings suggest that DCK can function as a potential novel prognostic biomarker and reflect the immune infiltration status in HCC patients.

Isolation and characterization of neural crest-like progenitor cells in human umbilical cord blood.

IntroductionNeural crest (NC)-like stem/progenitor cells provide an attractive cell source for regenerative medicine because of their multipotent property and ease of isolation from adult tissue. Although human umbilical cord blood (HUCB) is known to be a rich source of stem cells, the presence of the NC-like stem/progenitor cells in HUCB remains to be elucidated. In this study, we have isolated NC-like progenitor cells using an antibody to p75 neurotrophin receptor (p75NTR) and examined their phenotype and stem cell function in vitro.MethodsTo confirm whether p75NTR+ NC-derived cells are present in cord blood, flow cytometric analysis of cord blood derived from P0-Cre/Floxed-EGFP reporter mouse embryos was performed. Freshly isolated HUCB mononuclear cells was subjected to flow cytometry to detect p75NTR+ cells and determined their immunophenotype. HUCB p75NTR+ cells were then collected by immunomagnetic separation and their immunophenotype, clonogenic potential, gene expression profile, and multilineage differentiation potential were examined.ResultsNC-derived EGFP+ cells co-expressing p75NTR was detected in cord blood of P0-Cre/Floxed-EGFP reporter mice. We found that freshly isolated HUCB mononuclear cells contained 0.23% of p75NTR+ cells. Isolated p75NTR+ cells from HUCB efficiently formed neurospheres and could differentiate into neuronal and glial cell lineages. The p75NTR+ cells expressed a set of NC-associated genes and undifferentiated neural cell marker genes before and after the culture.ConclusionsThese findings revealed that HUCB contained the p75NTR+ NC-like progenitor cell population which have the self-renewal capacity and the potential to differentiate into both neuronal and glial cell lineages.

TGFβ2 is a prognostic-related biomarker and correlated with immune infiltrates in gastric cancer.

TGFβ2 is an essential regulator of immune cell functionality, but the mechanisms whereby it drives immune infiltration in gastric cancer remain uncertain. The Oncomine and Tumor Immunoassay Resource (TIMER) databases were used for assessing the expression of TGFβ2, after which TIMER was used to explore the relationship between TGFβ2 and tumour immune infiltration. Finally, we assessed how TGFβ2 expression correlated with the expression of a set of marker genes associated with immune infiltration using TIMER and GEPIA. We determined TGFβ2 expression to be significantly correlated with outcome in multiple types of cancer in the Cancer Genome Atlas (TCGA), with the effect being particularly pronounced in gastric cancer. Furthermore, elevated TGFβ2 expression was found to be significantly correlated with gastric cancer N staging, and with the expression of a variety of immune markers associated with particular immune cell subsets. These results indicate that TGFΒ2 is associated with patient outcome and tumour immune cell infiltration in multiple cancer types. This suggests that TGFβ2 is a key factor which governs immune cell recruitment to gastric cancer tumours, potentially playing a vital role in governing immune cell infiltration and thus representing a valuable prognostic biomarker in gastric cancer patients.

The role of SRGN in the survival and immune infiltrates of skin cutaneous melanoma (SKCM) and SKCM-metastasis patients

BackgroundSkin cutaneous melanoma (SKCM) is one of most aggressive type of cancers worldwide. Serglycin (SRGN) is an intracellular proteoglycan that playing an important role in various tumors. However, its effect on immune infiltrates and whether it associates with survival of SKCM and SKCM-metastasis patients has not been explored.MethodsWe evaluated SRGN expression via the databases of Oncomine, Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA). The influence of SRGN expression on survival of SKCM and SKCM-metastasis patients was analyzed using TIMER database. Furthermore, the correlations between SRGN expression and immune infiltrates or gene marker sets of immune infiltrates were also analyzed via TIMER database.ResultsWe found that the expression of SRGN in SKCM and SKCM-metastasis tissues was significantly increased compared to the normal skin tissues (P < 0.001). Interestingly, it was showed that lower level of SRGN expression and lower immune infiltrates of B cell, CD8+ T cell, Neutrophil, and Dendritic cell were correlated with poor survival rate of SKCM and SKCM-metastasis patients (P < 0.001) but not SKCM primary patients. We also demonstrated that SRGN expression was positively associated with the immune infiltrates and diverse immune marker sets in SKCM and SKCM-metastasis.ConclusionsOur findings indicated that SRGN was associated with the survival of SKCM and SKCM-metastasis patients. SRGN may be a new immune therapy target for treating SKCM and SKCM-metastasis.

Accurate estimation of cell composition in bulk expression through robust integration of single-cell information

We present Bisque, a tool for estimating cell type proportions in bulk expression. Bisque implements a regression-based approach that utilizes single-cell RNA-seq (scRNA-seq) or single-nucleus RNA-seq (snRNA-seq) data to generate a reference expression profile and learn gene-specific bulk expression transformations to robustly decompose RNA-seq data. These transformations significantly improve decomposition performance compared to existing methods when there is significant technical variation in the generation of the reference profile and observed bulk expression. Importantly, compared to existing methods, our approach is extremely efficient, making it suitable for the analysis of large genomic datasets that are becoming ubiquitous. When applied to subcutaneous adipose and dorsolateral prefrontal cortex expression datasets with both bulk RNA-seq and snRNA-seq data, Bisque replicates previously reported associations between cell type proportions and measured phenotypes across abundant and rare cell types. We further propose an additional mode of operation that merely requires a set of known marker genes.

Comparative Transcriptome Landscape of Mouse and Human Hearts.

Transcriptome landscape of organs from mice and humans offers perspectives on the process of how organs develop and the similarity and diversity in each organ between the species. Among multi-species and multi-organ dataset, which was previously generated, we focused on the mouse and human dataset and performed a reanalysis to provide a more specific perspective on the maturation of human cardiomyocytes. First, we examined how organs diversify their transcriptome during development across and within two species. We unexpectedly identified that ribosomal genes were differentially expressed between mice and humans. Second, we examined the corresponding ages of organs in mice and humans and found that the corresponding developmental ages did not match throughout organs. Mouse hearts at P0–3 and human hearts at 18–19 wpc showed the most proximity in the regard of the transcriptome. Third, we identified a novel set of maturation marker genes that are more consistent between mice and humans. In contrast, conventionally used maturation marker genes only work well with mouse hearts. Finally, we compared human pluripotent stem cell-derived cardiomyocytes (PSC-CMs) in maturation-enhanced conditions to human fetal and adult hearts and revealed that human PSC-CMs only expressed low levels of the potential maturation marker genes. Our findings provide a novel foundation to study cardiomyocyte maturation and highlight the importance of studying human samples rather than relying on a mouse time-series dataset.

Unearthing the Plant Growth-Promoting Traits of Bacillus megaterium RmBm31, an Endophytic Bacterium Isolated From Root Nodules of Retama monosperma.

Plants live in association with complex populations of microorganisms, including Plant Growth-Promoting Rhizobacteria (PGPR) that confer to plants an improved growth and enhanced stress tolerance. This large and diverse group includes endophytic bacteria that are able to colonize the internal tissues of plants. In the present study, we have isolated a nonrhizobial species from surface sterilized root nodules of Retama monosperma, a perennial leguminous species growing in poor and high salinity soils. Sequencing of its genome reveals this endophytic bacterium is a Bacillus megaterium strain (RmBm31) that possesses a wide range of genomic features linked to plant growth promotion. Furthermore, we show that RmBm31 is able to increase the biomass and positively modify the root architecture of seedlings of the model plant species Arabidopsis thaliana both in physical contact with its roots and via the production of volatile organic compounds. Lastly, we investigated the molecular mechanisms implicated in RmBm31 plant beneficial effects by carrying out a transcriptional analysis on a comprehensive set of phytohormone-responsive marker genes. Altogether, our results demonstrate that RmBm31 displays plant growth-promoting traits of potential interest for agricultural applications.

Phylogenomic Analyses of Members of the Widespread Marine Heterotrophic Genus Pseudovibrio Suggest Distinct Evolutionary Trajectories and a Novel Genus, Polycladidibacter gen. nov.

Bacteria belonging to the Pseudovibrio genus are widespread, metabolically versatile, and able to thrive as both free-living and host-associated organisms. Although more than 50 genomes are available, a comprehensive comparative genomics study to resolve taxonomic inconsistencies is currently missing. We analyzed all available genomes and used 552 core genes to perform a robust phylogenomic reconstruction. This in-depth analysis revealed the divergence of two monophyletic basal lineages of strains isolated from polyclad flatworm hosts, namely, Pseudovibrio hongkongensis and Pseudovibrio stylochi These strains have reduced genomes and lack sulfur-related metabolisms and major biosynthetic gene clusters, and their environmental distribution appears to be tightly associated with invertebrate hosts. We showed experimentally that the divergent strains are unable to utilize various sulfur compounds that, in contrast, can be utilized by the type strain Pseudovibrio denitrificans Our analyses suggest that the lineage leading to these two strains has been subject to relaxed purifying selection resulting in great gene loss. Overall genome relatedness indices (OGRI) indicate substantial differences between the divergent strains and the rest of the genus. While 16S rRNA gene analyses do not support the establishment of a different genus for the divergent strains, their substantial genomic, phylogenomic, and physiological differences strongly suggest a divergent evolutionary trajectory and the need for their reclassification. Therefore, we propose the novel genus Polycladidibacter gen. nov.IMPORTANCE The genus Pseudovibrio is commonly associated with marine invertebrates, which are essential for ocean health and marine nutrient cycling. Traditionally, the phylogeny of the genus has been based on 16S rRNA gene analysis. The use of the 16S rRNA gene or any other single marker gene for robust phylogenetic placement has recently been questioned. We used a large set of marker genes from all available Pseudovibrio genomes for in-depth phylogenomic analyses. We identified divergent monophyletic basal lineages within the Pseudovibrio genus, including two strains isolated from polyclad flatworms. These strains showed reduced sulfur metabolism and biosynthesis capacities. The phylogenomic analyses revealed distinct evolutionary trajectories and ecological adaptations that differentiate the divergent strains from the other Pseudovibrio members and suggest that they fall into a novel genus. Our data show the importance of widening the use of phylogenomics for better understanding bacterial physiology, phylogeny, and evolution.

FKBPL Is a Potential Prognostic Biomarker and Correlated with Immune Infiltrates and T Cells Exhaustion in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality and poor prognosis. And FKBPL plays a crucial role on the development of cancers. This study aims to explore the prognostic potential of FKBPL and comprehensively analyze the correlations between FKBPL, immune infiltration, and T cells function in HCC. GEO database, Oncomine databases, TIMER2.0 and GEPIA2 were used to analyze FKBPL expression, relationship between FKBPL expression and survival of HCC patients as well as immune infiltration, related gene marker sets and T cells exhaustion in HCC. We used STRING database to analysis PPI (protein-protein interaction) for FKBPL and visualization by Cytoscape. Metascape was used for enrichment analysis. FKBPL upregulates in most of the cancer types including HCC. Survival analysis demonstrated that FKBPL shows significant impact on survival of HCC patients with overall survival and disease-free survival. And survival rate of HCC patients with high FKBPL expression was significantly correlated with race, gender and tumor purity of HCC patients. Moreover, FKBPL expression positively correlates with high immune infiltration levels in most of the immune cells and functional T cells including exhausted T cells, Th1, Th2 and Tfh. Specifically, multiple key genes of exhausted T cells comprising PD-1, CTLA4, LAG3, TIM-3, and GZMB have remarkable interaction with FKBPL. At last, we found10 genes including PRRT1, ANKRD49, RBCK1, CSNK1D, HSP90AA1, HSP90AB1, GTSE1, CDKN1A, AVPR2, and EGFL8 were interacted with FKBPL. Enrichment analysis showed that apoptotic signaling pathway, regulation of myeloid cell differentiation, cell death in response to oxidative stress, PIP3 activates AKT signaling may involve in HCC tumor progression about FKBPL. In conclusion, FKBPL is a potential prognostic biomarker and correlated with immune infiltrates and T cells exhaustion in HCC.

DCK is an Unfavorable Prognostic Biomarker and Correlated With Immune Infiltrates in Liver Cancer.

Background:The biological function of deoxycytidine kinase in tumor is not yet clear, and there are a few studies relating to the correlation of deoxycytidine kinase gene with the occurrence and development of liver cancer.Methods:The messenger RNA expression of deoxycytidine kinase was analyzed with the use of the UALCAN and GEPIA database. Moreover, we assessed the function of deoxycytidine kinase on clinical prognosis with Kaplan-Meier plotter database. The relationship between deoxycytidine kinase and cancer immune infiltrates was investigated via Tumor Immune Estimation Resource site. Furthermore, Tumor Immune Estimation Resource was also used to evaluate the correlations between the expression of deoxycytidine kinase and gene marker sets of immune infiltrates.Results:The deoxycytidine kinase messenger RNA level significantly upregulated in patients with liver cancer compared to normal liver samples. Moreover, the increased expression of deoxycytidine kinase messenger RNA was closely associated with reduced overall survival and disease-free survival in all liver cancers. In addition, deoxycytidine kinase expression displayed a strong correlation with infiltrating levels of macrophages, neutrophils, and dendritic cells in liver cancer, and deoxycytidine kinase expression was positively correlated with diverse immune marker sets in liver cancer.Conclusions:All the above findings suggested that increased expression of deoxycytidine kinase was significantly related to unfavorable prognosis in patients with liver cancer. And deoxycytidine kinase is correlated with immune infiltrating levels, including those of B cells, macrophages, neutrophils, and dendritic cells in patients with liver cancer. These findings suggest that deoxycytidine kinase can be used as a prognostic biomarker for determining prognosis and immune infiltration in liver cancer. And deoxycytidine kinase is a potential target for liver cancer therapy, and these preliminary findings require further study to determine whether deoxycytidine kinase-targeting reagents might be developed for clinical application in liver cancer.

Fast identification of Escherichia coli in urinary tract infections using a virulence gene based PCR approach in a novel thermal cycler

Uropathogenic Escherichia coli (UPEC) is the most common causal agent of urinary tract infections (UTIs) in humans. Currently, clinical detection methods take hours (dipsticks) to days (culturing methods), limiting rapid intervention. As an alternative, the use of molecular methods could improve speed and accuracy, but their applicability is complicated by high genomic variability within UPEC strains. Here, we describe a novel PCR-based method for the identification of E. coli in urine. Based on in silico screening of UPEC genomes, we selected three UPEC-specific genes predicted to be involved in pathogenesis (c3509, c3686 (yrbH) and chuA), and one E. coli-specific marker gene (uidA). We validated the method on 128 clinical (UTI) strains. Despite differential occurrences of these genes in uropathogenic E. coli, the method, when using multi-gene combinations, specifically detected the target organism across all samples. The lower detection limit, assessed with model UPEC strains, was approximately 104 CFU/ml. Additionally, the use of this method in a novel ultrafast PCR thermal cycler (Nextgen PCR) allowed a detection time from urine sampling to identification of only 52 min. This is the first study that uses such defined sets of marker genes for the detection of E. coli in UTIs. In addition, we are the first to demonstrate the potential of the Nextgen thermal cycler. Our E. coli identification method has the potential to be a rapid, reliable and inexpensive alternative for traditional methods.

The subgingival microbiome associated with periodontitis in type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) is a systemic disease, predisposing patients to other inflammatory conditions including periodontitis. The subgingival microbiome, a key player in periodontitis pathogenesis, is not well characterized in T2DM population. To better understand whether the subgingival microbiome is different between T2DM and systemically healthy, nondiabetic (ND) subjects, we performed a longitudinal analysis of the subgingival microbiome in T2DM patients (n = 15) compared with ND subjects (n = 16). Using metagenomic shotgun sequencing, we investigated the microbiome in the healthy periodontal state, periodontitis state, and resolved state after treatment. We found that in the periodontitis state, the shift in the subgingival microbiome from the healthy state was less prominent in T2DM compared with ND subjects, yet the clinical signs of disease were similar for both. Furthermore, we revealed highly correlated presence of pathogenic species in relative abundance not only in the periodontitis state, but also in the healthy state in T2DM, suggesting an elevated risk of progression to periodontitis in this cohort. We further investigated the functional potentials of the subgingival microbiome and identified a set of microbial marker genes associated with the clinical states. These genes were significantly enriched in 21 pathways, some of which are associated with periodontitis and some potentially link T2DM and periodontitis. This study identified the longitudinal changes of the subgingival microbiome associated with periodontitis in T2DM and suggests that T2DM patients are more susceptible to shifts in the subgingival microbiome toward dysbiosis, potentially due to impaired host metabolic and immune regulation.

Providencia entomophila sp. nov., a new bacterial species associated with major olive pests in Tunisia.

Bioprospection for potential microbial biocontrol agents associated with three major insect pests of economic relevance for olive cultivation in the Mediterranean area, namely the olive fly, Bactrocera oleae, the olive moth, Prays oleae, and the olive psyllid, Euphyllura olivina, led to the isolation of several strains of readily cultivable Gram-negative, rod-shaped bacteria from Tunisian olive orchards. Determination of 16S ribosomal RNA encoding sequences identified the bacteria as members of the taxonomic genus Providencia (Enterobacterales; Morganellaceae). A more detailed molecular taxonomic analysis based on a previously established set of protein-encoding marker genes together with DNA-DNA hybridization and metabolic profiling studies led to the conclusion that the new isolates should be organized in a new species within this genus. With reference to their original insect association, the designation “Providencia entomophila” is proposed here for this hypothetical new taxon.

Emerging threat ofEimeriaoperational taxonomic units (OTUs) on poultry production

Coccidiosis is an antagonistic poultry disease which negatively impacts animal welfare and productivity. The disease is caused by an obligate, intracellular protozoon known as Eimeria. Several Eimeria species known to infect chickens have been well documented. However, recent studies have elucidated the emergence of three novel genetic variants or operational taxonomic units (OTUs). The discovery of OTUx, OTUy and OTUz complicates the identification and diagnosis of coccidiosis. OTUs are clusters of unknown or uncultivated organisms that are grouped according to a similarity in DNA sequence to a set of specific gene markers. OTUs have been reported in the Earth's Southern Hemisphere, including Australia, Venezuela, India, Zambia, Uganda, Tanzania, China and Ghana. Elucidating their impact on the poultry industry is fundamental in preventing anticoccidial resistance and to access the potential of OTUs as vaccine candidates to provide cross-protection against similar Eimeria species. The identification of OTUs further decreases the risk of false negative coccidial diagnosis. Therefore, this article reviews the importance and risk imposed by OTUs, coupled with their prevalence and geographical distribution in chickens globally.

In silico Identification of Serovar-Specific Genes for Salmonella Serotyping.

Salmonella enterica subspecies enterica is a highly diverse subspecies with more than 1500 serovars and the ability to distinguish serovars within this group is vital for surveillance. With the development of whole-genome sequencing technology, serovar prediction by traditional serotyping is being replaced by molecular serotyping. Existing in silico serovar prediction approaches utilize surface antigen encoding genes, core genome MLST and serovar-specific gene markers or DNA fragments for serotyping. However, these serovar-specific gene markers or DNA fragments only distinguished a small number of serovars. In this study, we compared 2258 Salmonella accessory genomes to identify 414 candidate serovar-specific or lineage-specific gene markers for 106 serovars which includes 24 polyphyletic serovars and the paraphyletic serovar Enteritidis. A combination of several lineage-specific gene markers can be used for the clear identification of the polyphyletic serovars and the paraphyletic serovar. We designed and evaluated an in silico serovar prediction approach by screening 1089 genomes representing 106 serovars against a set of 131 serovar-specific gene markers. The presence or absence of one or more serovar-specific gene markers was used to predict the serovar of an isolate from genomic data. We show that serovar-specific gene markers have comparable accuracy to other in silico serotyping methods with 84.8% of isolates assigned to the correct serovar with no false positives (FP) and false negatives (FN) and 10.5% of isolates assigned to a small subset of serovars containing the correct serovar with varied FP. Combined, 95.3% of genomes were correctly assigned to a serovar. This approach would be useful as diagnosis moves to culture-independent and metagenomic methods as well as providing a third alternative to confirm other genome-based analyses. The identification of a set of gene markers may also be useful in the development of more cost-effective molecular assays designed to detect specific gene markers of the all major serovars in a region. These assays would be useful in serotyping isolates where cultures are no longer obtained and traditional serotyping is therefore impossible.

Limb specific Acvr1-knockout during embryogenesis in mice exhibits great toe malformation as seen in Fibrodysplasia Ossificans Progressiva (FOP).

PurposeThis study analyzes Prx1‐specific conditional knockout of Acvr1 aiming to elucidate the endogenous role of Acvr1 during limb formation in early embryonic development. ACVR1 can exhibit activating and inhibiting function in BMP signaling. ACVR1 gain‐of‐function mutations can cause the rare disease fibrodysplasia ossificans progressiva (FOP), where patients develop ectopic bone replacing soft tissue, tendons and ligaments.MethodsWhole‐mount in situ hybridization and skeletal preparations revealed that following limb‐specific conditional knockout of Acvr1, metacarpals and proximal phalanges were shortened and additional cartilage and bone elements were formed.ResultsThe analysis of a set of marker genes including ligands and receptors of BMP signaling as well as genes involved in patterning and tendon and cartilage formation, revealed temporal disturbances with distinct spatial patterns. The most striking result was that in the absence of Acvr1 in mesoderm precursor cells, first digits were drastically malformed.ConclusionIn FOP, malformation of big toes can serve as a first soft marker in diagnostics. The surprising similarities in phenotype between the described conditional knockout of Acvr1 and the FOP mouse model, indicates a natural inhibitory function of ACVR1. This represents a further step towards better understanding the role of Acvr1 and developing treatment options for FOP.

Combined surgery and chondrocyte cell-sheet transplantation improves clinical and structural outcomes in knee osteoarthritis

Current cartilage regenerative therapies are not fully effective in treating osteoarthritis of the knee (OAK). We have developed chondrocyte sheets for autologous transplantation and tested these in in vitro and in vivo preclinical studies, and have reported that the transplantation of chondrocyte sheets promoted hyaline cartilage repair in rat, rabbit, and minipig models. However, autologous transplantation of chondrocyte sheets has yet to be reported in humans. Here, we report our combination therapy in which conventional surgical treatment for OAK, is followed by autologous chondrocyte sheet transplantation for cartilage repair. Eight patients with OAK and cartilage defects categorized arthroscopically as Outerbridge grade III or IV receive the therapy. Patients are thoroughly assessed by preoperative and postoperative X-rays, magnetic resonance imaging (MRI), arthroscopy, Knee injury and Osteoarthritis Outcome Score (KOOS), Lysholm Knee Score (LKS), and a laser-induced photoacoustic method to assess cartilage viscoelasticity. Arthroscopic biopsies of all patients are performed 12 months after transplantation for histological evaluation. The properties of the chondrocyte sheets are evaluated using gene expression analysis to investigate the ability to predict the clinical and structural outcomes of the therapy. For this small initial longitudinal series, combination therapy is effective, as assessed by MRI, arthroscopy, viscoelasticity, histology, and the clinical outcomes of KOOS and LKS. Gene marker sets identified in autologous chondrocyte sheets may be predictive of the overall KOOS, LKS, and histological scores after therapy. These predictive gene sets may be potential alternative markers for evaluating OAK treatment.