Application of the random forest algorithm to Streptococcus pyogenes response regulator allele variation: from machine learning to evolutionary models

Group A Streptococcus (GAS) is a globally significant bacterial pathogen. The GAS genotyping gold standard characterises the nucleotide variation of emm, which encodes a surface-exposed protein that is recombinogenic and under immune-based selection pressure. Within a supervised learning methodology, we tested three random forest (RF) algorithms (Guided, Ordinary, and Regularized) and 53 GAS response regulator (RR) allele types to infer six genomic traits (emm-type, emm-subtype, tissue and country of sample, clinical outcomes, and isolate invasiveness). The Guided, Ordinary, and Regularized RF classifiers inferred the emm-type with accuracies of 96.7%, 95.7%, and 95.2%, using ten, three, and four RR alleles in the feature set, respectively. Notably, we inferred the emm-type with 93.7% accuracy using only mga2 and lrp. We demonstrated a utility for inferring emm-subtype (89.9%), country (88.6%), invasiveness (84.7%), but not clinical (56.9%), or tissue (56.4%), which is consistent with the complexity of GAS pathophysiology. We identified a novel cell wall-spanning domain (SF5), and proposed evolutionary pathways depicting the ‘contrariwise’ and ‘likewise’ chimeric deletion-fusion of emm and enn. We identified an intermediate strain, which provides evidence of the time-dependent excision of mga regulon genes. Overall, our workflow advances the understanding of the GAS mga regulon and its plasticity.

Interferon-stimulated and metallothionein-expressing macrophages are associated with acute and chronic allograft dysfunction after lung transplantation

Lung transplant (LT) recipients experience episodes of immune-mediated acute lung allograft dysfunction (ALAD). ALAD episodes are a risk factor for chronic lung allograft dysfunction (CLAD), the major cause of death after LT. We have applied single-cell RNA sequencing (scRNAseq) to bronchoalveolar lavage (BAL) cells from stable and ALAD patients and to cells from explanted CLAD lung tissue to determine key cellular elements in dysfunctional lung allografts, with a focus on macrophages. We identified two alveolar macrophage (AM) subsets uniquely represented in ALAD. Using pathway analysis and differentially expressed genes, we annotated these as pro-inflammatory interferon-stimulated gene (ISG) and metallothionein-mediated inflammatory (MT) AMs. Functional analysis of an independent set of AMs in vitro revealed that ALAD AMs exhibited a higher expression of CXCL10, a marker of ISG AMs, and increased secretion of pro-inflammatory cytokines compared to AMs from stable patients. Using publicly available BAL scRNAseq datasets, we found that ISG and MT AMs are associated with more severe inflammation in COVID-19 patients. Analysis of cells from four explanted CLAD lungs revealed similar macrophage populations. Using a single nucleotide variation calling algorithm, we also demonstrate contributions of donor and recipient cells to all AM subsets early post-transplant, with loss of donor-derived cells over time. Our data reveals extensive heterogeneity among lung macrophages after LT and indicates that specific sub-populations may be associated with allograft dysfunction, raising the possibility that these cells may represent important therapeutic targets.

PCR-RFLP molecular confirmation of color dilution alopecia in dogs in Brazil

Color dilution alopecia (CDA) is a dermatopathy observed exclusively in animals having a diluted coat color. In dogs, color dilution occurs as a result of a single-nucleotide variation (SNV) c.-22G > A in the melanophilin gene. We standardized a PCR–restriction-fragment length polymorphism (PCR-RFLP) technique to identify this mutation and determine its frequency in dogs in Brazil. The standardized PCR-RFLP technique could efficiently identify the SNV c.-22G > A in the melanophilin gene, with mutated allele frequencies of 0.1, 0.1, and 0.0875 in Dachshund, Miniature Pinscher, and Yorkshire Terrier breeds, respectively, with no statistical difference among the breeds ( p = 0.252). The mutation was identified in 2 homozygous Dachshund dogs with alopecia, confirming the clinical characteristic of CDA. The standardization of a simpler and more accessible molecular technique for recognition of the SNV c.-22G > A in the melanophilin gene allows identification of heterozygous (phenotypically normal) dogs that can be excluded from reproduction, to avoid the birth of dogs with diluted coat color and consequently CDA.

Transposable element accumulation drives size differences among polymorphic Y chromosomes in Drosophila

Y chromosomes of many species are gene poor and show low levels of nucleotide variation, yet often display high amounts of structural diversity. Dobzhansky cataloged several morphologically distinct Y chromosomes in Drosophila pseudoobscura that differ in size and shape, but the molecular causes of their dramatic size differences are unclear. Here we use cytogenetics and long-read sequencing to study the sequence content of polymorphic Y chromosomes in D. pseudoobscura. We show that Y chromosomes differ by almost 2-fold in size, ranging from 30 to 60 Mb. Most of this size difference is caused by a handful of active transposable elements (TEs) that have recently expanded on the largest Y chromosome, with different elements being responsible for Y expansion on differently sized D. pseudoobscura Ys. We show that Y chromosomes differ in their heterochromatin enrichment, expression of Y-enriched TEs, and also influence expression of dozens of autosomal and X-linked genes. Intriguingly, the same helitron element that showed the most drastic amplification on the largest Y in D. pseudoobscura independently amplified on a polymorphic large Y chromosome in D. affinis, suggesting that some TEs are inherently more prone to become deregulated on Y chromosomes.

Genetic and tumor microenvironment differences between cell cycle progression pathway altered/non-altered patients with lung adenocarcinoma

Background Lung cancer is the leading cause of cancer-related death worldwide, among which lung adenocarcinoma (LUAD) is the most common type. Identified as a hallmark of cancer, the dysregulated cell cycle progression plays an important role in the promotion and progression of LUAD. This article aims to elucidate the heterogeneity between CDKN2A-CDK/cyclin-RB1 cell cycle progression pathway altered /non-altered patients with LUAD, thus helping us have a better understanding of the effect of the aberrant cell cycle. Material and Methods The data of this study were downloaded from The Cancer Genome Atlas (TCGA) data portal (https://portal.gdc.cancer.gov/) and UCSC Xena Browser (http://xena.ucsc.edu/), including simple nucleotide variation data, RNA-seq gene expression data, survival data, clinical data, and miRNA expression data. After matching the RNA-seq gene expression data, simple nucleotide variation data, miRNA expression data, and survival data with clinical data, 510 gene and long non-coding RNA expression data, 506 simple nucleotide variation data, 440 microRNA expression data, and 497 survival data were included in this study for further analysis. R software (version 4.0.3) was used for analysis. Results After dividing the patients into mutation (n = 57) and wild (n = 453) groups according to the cell cycle progression pathway status, we found no significant difference in survivorship between them. The mutation group had a higher mutational load and mutational rates of various genes such as tumor protein P53 (TP53) compared to the wild group. Subsequently, we analyzed the differentially expressed genes (DEGs) between the two groups. Among the 58387 genes analyzed, 302 were upregulated, and 354 were downregulated in the mutation group. Enrichment analysis indicated that these DEGs were closely related to metabolism items and cell cycle-related events. After performing immune cell infiltration analysis, we found the two groups have different patterns of immune cell profiling. Albeit the immune and stromal scores were higher in the wild group, we failed to find any significant difference between the two groups. Finally, we build a computational model to predict the cell cycle progression pathway-related gene mutation by LASSO-binary logistic regression analysis, the predictive accuracy of which is 0.88. Conclusion In summary, our study compared the genetic and microenvironment differences between cell cycle progression pathway altered /non-altered patients with LUAD by analyzing the data from TCGA datasets. We hope our findings could improve our understanding of the heterogeneity between the two kinds of patients, thus providing new insight into LUAD patients' treatments.