A genome phylogeny for mitochondria among alpha-proteobacteria and a predominantly eubacterial ancestry of yeast nuclear genes

Analyses of 55 individual and 31 concatenated protein data sets encoded in Reclinomonas americana and Marchantia polymorpha mitochondrial genomes revealed that current methods for constructing phylogenetic trees are insufficiently sensitive (or artifact-insensitive) to ascertain the sister of mitochondria among the current sample of eight alpha-proteobacterial genomes using mitochondrially-encoded proteins. However, Rhodospirillum rubrum came as close to mitochondria as any alpha-proteobacterium investigated. This prompted a search for methods to directly compare eukaryotic genomes to their prokaryotic counterparts to investigate the origin of the mitochondrion and its host from the standpoint of nuclear genes. We examined pairwise amino acid sequence identity in comparisons of 6,214 nuclear protein-coding genes from Saccharomyces cerevisiae to 177,117 proteins encoded in sequenced genomes from 45 eubacteria and 15 archaebacteria. The results reveal that approximately 75% of yeast genes having homologues among the present prokaryotic sample share greater amino acid sequence identity to eubacterial than to archaebacterial homologues. At high stringency comparisons, only the eubacterial component of the yeast genome is detectable. Our findings indicate that at the levels of overall amino acid sequence identity and gene content, yeast shares a sister-group relationship with eubacteria, not with archaebacteria, in contrast to the current phylogenetic paradigm based on ribosomal RNA. Among eubacteria and archaebacteria, proteobacterial and methanogen genomes, respectively, shared more similarity with the yeast genome than other prokaryotic genomes surveyed

The piRNA-pathway factor FKBP6 is essential for spermatogenesis but dispensable for control of meiotic LINE-1 expression in humans

Infertility affects around 7% of the male population and can be due to severe spermatogenic failure (SPGF), resulting in no or very few sperm in the ejaculate. We initially identified a homozygous frameshift variant in FKBP6 in a man with extreme oligozoospermia. Subsequently, we screened a total of 2,699 men with SPGF and detected rare bi-allelic loss-of-function variants in FKBP6 in five additional persons. All six individuals had no or extremely few sperm in the ejaculate, which were not suitable for medically assisted reproduction. Evaluation of testicular tissue revealed an arrest at the stage of round spermatids. Lack of FKBP6 expression in the testis was confirmed by RT-qPCR and immunofluorescence staining. In mice, Fkbp6 is essential for spermatogenesis and has been described as being involved in piRNA biogenesis and formation of the synaptonemal complex (SC). We did not detect FKBP6 as part of the SC in normal human spermatocytes, but small RNA sequencing revealed that loss of FKBP6 severely impacted piRNA levels, supporting a role for FKBP6 in piRNA biogenesis in humans. In contrast to findings in piRNA-pathway mouse models, we did not detect an increase in LINE-1 expression in men with pathogenic FKBP6 variants. Based on our findings, FKBP6 reaches a "strong" level of evidence for being associated with male infertility according to the ClinGen criteria, making it directly applicable for clinical diagnostics. This will improve patient care by providing a causal diagnosis and will help to predict chances for successful surgical sperm retrieval

The sulfur pathway and diagnosis of sulfate depletion in grapevine

Sulfur is an essential nutrient to all plant species. Plants assimilate sulfur in a well-described pathway, which has been taken up by roots. Regulatory mech- anism has been the subject of many research papers. However, recent studies highlighted differences between crop plants and the model plant Arabidopsis thaliana. Our work focuses on the identification of genes involved in the sulfur metabolism in the Vitis vinifera genome, and their response to sulfur deficiency and other abiotic stress endured by grapevine in the field, namely water stress. Here, we describe the identification and brief characterization of the first assimilation enzymes involved in the sulfur pathway, the enzyme responsible for sulfur activa- tion, ATP sulfurylase (ATPS), and the two enzymes that reduce sulfate to sulfide, Adenosine 50-phosphosulate reductase (APR) and Sulfite reductase (SiR). A reduc- tion was observed in the number of ATPS and APR isoforms identified in V. vinifera genome when compared to A. thaliana or Glycine max genomes. Two ATPS isoforms were present in the Vitis genome, of which only ATPS1 transcript was detected in the tested tissues, and one APR isoform, suggesting an absence of redundancy in the role of both enzymes. ATPS1, APR and SiR transcript level was up-regulated in response to 2 days exposure to sulfur deficiency in V. vinifera cell cultures, which was completely reversed by the addition of GSH to the culture medium. Apparently, oxidative stress triggered GSH has a pivotal role in the regulation of ATPS1, APR and SiR transcription level, since their up-regulation was observed in mRNA from field grapevine berries under water stress, which is known to induce oxidative stress.info:eu-repo/semantics/publishedVersio

Complex machine-learning algorithms and multivariable logistic regression on par in the prediction of insufficient clinical response to methotrexate in rheumatoid arthritis

The goals of this study were to examine whether machine-learning algorithms outper-form multivariable logistic regression in the prediction of insufficient response to methotrexate (MTX); secondly, to examine which features are essential for correct prediction; and finally, to in-vestigate whether the best performing model specifically identifies insufficient responders to MTX (combination) therapy. The prediction of insufficient response (3-month Disease Activity Score 28-Erythrocyte-sedimentation rate (DAS28-ESR) > 3.2) was assessed using logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting (XGBoost). The baseline features of 355 rheumatoid arthritis (RA) patients from the “treatment in the Rotterdam Early Arthritis CoHort” (tREACH) and the U-Act-Early trial were combined for analyses. The model performances were compared using area under the curve (AUC) of receiver operating characteristic (ROC) curves, 95% confidence intervals (95% CI), and sensitivity and specificity. Fi-nally, the best performing model following feature selection was tested on 101 RA patients starting tocilizumab (TCZ)-monotherapy. Logistic regression (AUC = 0.77 95% CI: 0.68–0.86) performed as well as LASSO (AUC = 0.76, 95% CI: 0.67–0.85), random forest (AUC = 0.71, 95% CI: 0.61 = 0.81), and XGBoost (AUC = 0.70, 95% CI: 0.61–0.81), yet logistic regression reached the highest sensitivity (81%). The most important features were baseline DAS28 (components). For all algorithms, models with six features performed similarly to those with 16. When applied to the TCZ-monotherapy group, logistic regression’s sensitivity significantly dropped from 83% to 69% (p = 0.03). In the current dataset, logistic regression performed equally well compared to machine-learning algorithms in the prediction of insufficient response to MTX. Models could be reduced to six features, which are more conducive for clinical implementation. Interestingly, the prediction model was specific to MTX (combination) therapy response

Analysis of copy number variation in men with non-obstructive azoospermia

BACKGROUND: Recent findings demonstrate that single nucleotide variants can cause non-obstructive azoospermia (NOA). In contrast, copy number variants (CNVs) were only analysed in few studies in infertile men. Some have reported a higher prevalence of CNVs in infertile versus fertile men. OBJECTIVES: This study aimed to elucidate if CNVs are associated with NOA. MATERIALS AND METHODS: We performed array-based comparative genomic hybridization (aCGH) in 37 men with meiotic arrest, 194 men with Sertoli cell-only phenotype, and 21 control men. We filtered our data for deletions affecting genes and prioritized the affected genes according to a literature search. Prevalence of CNVs was compared between all groups. Exome data of 2,030 men were screened to detect further genetic variants in prioritized genes. Modelling was performed for the protein encoded by the novel candidate gene TEKT5 and we stained for TEKT5 in human testicular tissue. RESULTS: We determined the cause of infertility in two individuals with homozygous deletions of SYCE1 and in one individual with a heterozygous deletion of SYCE1 combined with a likely pathogenic missense variant on the second allele. We detected heterozygous deletions affecting MLH3, EIF2B2, SLX4, CLPP and TEKT5, in one subject each. CNVs were not detected more frequently in infertile men compared with controls. DISCUSSION: While SYCE1 and MLH3 encode known meiosis-specific proteins, much less is known about the proteins encoded by the other identified candidate genes, warranting further analyses. We were able to identify the cause of infertility in one out of the 231 infertile men by aCGH and in two men by using exome sequencing data. CONCLUSION: As aCGH and exome sequencing are both expensive methods, combining both in a clinical routine is not an effective strategy. Instead, using CNV calling from exome data has recently become more precise, potentially making aCGH dispensable

Axisymmetric compressible boundary layer on a long thin moving cylinder

The steady laminar boundary layer flow on a thin and isothermal moving cylinder in a viscous compressible fluid at rest is studied in this paper. The fluid considered is a model fluid in which ϱ∼ T −1 and μ∼ T ω . The transformed non-similar boundary layer equations are solved numerically using a very efficient numerical method for some values of ω and wall enthalpy g ω parameters. The skin friction coefficient and Nusselt number are calculated for Pr=0.7 and some values of ω and g ωPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41705/1/707_2005_Article_BF01291848.pd

Precision medicine driven by cancer systems biology

Molecular insights from genome and systems biology are influencing how cancer is diagnosed and treated. We critically evaluate big data challenges in precision medicine. The melanoma research community has identified distinct subtypes involving chronic sun-induced damage and the mitogen-activated protein kinase driver pathway. In addition, despite low mutation burden, non-genomic mitogen-activated protein kinase melanoma drivers are found in membrane receptors, metabolism, or epigenetic signaling with the ability to bypass central mitogen-activated protein kinase molecules and activating a similar program of mitogenic effectors. Mutation hotspots, structural modeling, UV signature, and genomic as well as non-genomic mechanisms of disease initiation and progression are taken into consideration to identify resistance mutations and novel drug targets. A comprehensive precision medicine profile of a malignant melanoma patient illustrates future rational drug targeting strategies. Network analysis emphasizes an important role of epigenetic and metabolic master regulators in oncogenesis. Co-occurrence of driver mutations in signaling, metabolic, and epigenetic factors highlights how cumulative alterations of our genomes and epigenomes progressively lead to uncontrolled cell proliferation. Precision insights have the ability to identify independent molecular pathways suitable for drug targeting. Synergistic treatment combinations of orthogonal modalities including immunotherapy, mitogen-activated protein kinase inhibitors, epigenetic inhibitors, and metabolic inhibitors have the potential to overcome immune evasion, side effects, and drug resistance