Myo1c is an unconventional myosin involved in cell signaling and membrane dynamics. Calcium binding to the regulatory-domain-associated calmodulin affects myo1c motor properties, but the kinetic details of this regulation are not fully understood. We performed actin gliding assays, ATPase measurements, fluorescence spectroscopy, and stopped-flow kinetics to determine the biochemical parameters that define the calmodulin-regulatory-domain interaction. We found calcium moderately increases the actin-activated ATPase activity and completely inhibits actin gliding. Addition of exogenous calmodulin in the presence of calcium fully restores the actin gliding rate. A fluorescently labeled calmodulin mutant (N111C) binds to recombinant peptides containing the myo1c IQ motifs at a diffusion-limited rate in the presence and absence of calcium. Measurements of calmodulin dissociation from the IQ motifs in the absence of calcium show that the calmodulin bound to the IQ motif adjacent to the motor domain (IQ1) has the slowest dissociation rate (0.0007 s -1 ), and the IQ motif adjacent to the tail domain (IQ3) has the fastest dissociation rate (0.5 s -1 ). When the complex is equilibrated with calcium, calmodulin dissociates most rapidly from IQ1 (60 s -1 ). However, this increased rate of dissociation is limited by a slow calcium-induced conformational change (3 s -1 ). Fluorescence anisotropy decay of fluorescently labeled N111C bound to myo1c did not depend appreciably on Ca 2+ . Our data suggest that the calmodulin bound to the IQ motif adjacent to the motor domain is rapidly exchangeable in the presence of calcium and is responsible for regulation of myo1c ATPase and motile activity.

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Genomic aberrations and gene expression-defined subtypes in the large METABRIC patient cohort have been used to stratify and predict survival. The present study used normalized gene expression signatures of paclitaxel drug response to predict outcome for different survival times in METABRIC patients receiving hormone (HT) and, in some cases, chemotherapy (CT) agents. This machine learning method, which distinguishes sensitivity vs. resistance in breast cancer cell lines and validates predictions in patients; was also used to derive gene signatures of other HT  (tamoxifen) and CT agents (methotrexate, epirubicin, doxorubicin, and 5-fluorouracil) used in METABRIC. Paclitaxel gene signatures exhibited the best performance, however the other agents also predicted survival with acceptable accuracies. A support vector machine (SVM) model of paclitaxel response containing genes  ABCB1, ABCB11, ABCC1, ABCC10, BAD, BBC3, BCL2, BCL2L1, BMF, CYP2C8, CYP3A4, MAP2, MAP4, MAPT, NR1I2, SLCO1B3, TUBB1, TUBB4A, and TUBB4B was 78.6% accurate in predicting survival of 84 patients treated with both HT and CT (median survival ≥ 4.4 yr). Accuracy was lower (73.4%) in 304 untreated patients. The performance of other machine learning approaches was also evaluated at different survival thresholds. Minimum redundancy maximum relevance feature selection of a paclitaxel-based SVM classifier based on expression of genes  BCL2L1, BBC3, FGF2, FN1, and  TWIST1  was 81.1% accurate in 53 CT patients. In addition, a random forest (RF) classifier using a gene signature ( ABCB1, ABCB11, ABCC1, ABCC10, BAD, BBC3, BCL2, BCL2L1, BMF, CYP2C8, CYP3A4, MAP2, MAP4, MAPT, NR1I2,SLCO1B3, TUBB1, TUBB4A, and TUBB4B) predicted >3-year survival with 85.5% accuracy in 420 HT patients. A similar RF gene signature showed 82.7% accuracy in 504 patients treated with CT and/or HT. These results suggest that tumor gene expression signatures refined by machine learning techniques can be useful for predicting survival after drug therapies.

Biliary atresia (BA) results in severe bile blockage and is caused by the absence of extrahepatic ducts. Even after successful hepatic portoenterostomy, a considerable number of patients are likely to show progressive deterioration in liver function. Recent studies show that mutations in protein-coding mitochondrial DNA (mtDNA) genes and/or mitochondrial genes in nuclear DNA (nDNA) are associated with hepatocellular dysfunction. This observation led us to investigate whether hepatic dysfunctions in BA is genetically associated with mtDNA mutations. We sequenced the mtDNA protein-coding genes in 14 liver specimens from 14 patients with BA and 5 liver specimens from 5 patients with choledochal cyst using next-generation sequencing. We found 34 common non-synonymous variations in mtDNA protein-coding genes in all patients examined. A systematic 3D structural analysis revealed the presence of several single nucleotide polymorphism-like mutations in critical regions of complexes I to V, that are involved in subunit assembly, proton-pumping activity, and/or supercomplex formation. The parameters of chronic hepatic injury and liver dysfunction in BA patients were also significantly correlated with the extent of hepatic failure, suggesting that the mtDNA mutations may aggravate hepatopathy. Therefore, mitochondrial mutations may underlie the pathological mechanisms associated with BA.

The velvet regulator VosA plays a pivotal role in asexual sporulation in the model filamentous fungus Aspergillus nidulans. In the present study, we characterize the roles of VosA in sexual spores (ascospores) in A. nidulans. During ascospore maturation, the deletion of vosA causes a rapid decrease in spore viability. The absence of vosA also results in a lack of trehalose biogenesis and decreased tolerance of ascospores to thermal and oxidative stresses. RNA-seq-based genome-wide expression analysis demonstrated that the loss of vosA leads to elevated expression of sterigmatocystin (ST) biosynthetic genes and a slight increase in ST production in ascospores. Moreover, the deletion of vosA causes upregulation of additional gene clusters associated with the biosynthesis of other secondary metabolites, including asperthecin, microperfuranone, and monodictyphenone. On the other hand, the lack of vosA results in the downregulation of various genes involved in primary metabolism. In addition, vosA deletion alters mRNA levels of genes associated with the cell wall integrity and trehalose biosynthesis. Overall, these results demonstrate that the velvet regulator VosA plays a key role in the maturation and the cellular and metabolic integrity of sexual spores in A. nidulans.

Variable region analysis of 16S rRNA gene sequences is the most common tool in bacterial taxonomic studies. Although used for distinguishing bacterial species, its use remains limited due to the presence of variable copy numbers with sequence variation in the genomes. In this study, 16S rRNA gene sequences, obtained from completely assembled whole genome and Sanger electrophoresis sequencing of cloned PCR products from Serratia fonticola GS2, were compared. Sanger sequencing produced a combination of sequences from multiple copies of 16S rRNA genes. To determine whether the variant copies of 16S rRNA genes affected Sanger sequencing, two ratios (5:5 and 8:2) with different concentrations of cloned 16S rRNA genes were used; it was observed that the greater the number of copies with similar sequences the higher its chance of amplification. Effect of multiple copies for taxonomic classification of 16S rRNA gene sequences was investigated using the strain GS2 as a model. 16S rRNA copies with the maximum variation had 99.42% minimum pairwise similarity and this did not have an effect on species identification. Thus, PCR products from genomes containing variable 16S rRNA gene copies can provide sufficient information for species identification except from species which have high similarity of sequences in their 16S rRNA gene copies like the case of Bacillus thuringiensis and Bacillus cereus . In silico analysis of 1,616 bacterial genomes from long-read sequencing was also done. The average minimum pairwise similarity for each phylum was reported with their average genome size and average “unique copies” of 16S rRNA genes and we found that the phyla Proteobacteria and Firmicutes showed the highest amount of variation in their copies of their 16S rRNA genes. Overall, our results shed light on how the variations in the multiple copies of the 16S rRNA genes of bacteria can aid in appropriate species identification.

The possible roles of PUFAs pathways, such as those mediated by fatty acid synthase, polyketide synthase, and desaturase/elongase, co-exist in S. mangrovei PQ6.

Although emerging evidence revealed that the gut microbiome served as a tool and as biomarkers for predicting and detecting specific cancer or illness, it is yet unknown if vaginal microbiome-derived bacterial markers can be used as a predictive model to predict the severity of CIN. In this study, we sequenced V3 region of 16S rRNA gene on vaginal swab samples from 66 participants (24 CIN 1−, 42 CIN 2+ patients) and investigated the taxonomic composition. The vaginal microbial diversity was not significantly different between the CIN 1− and CIN 2+ groups. However, we observed Lactobacillus amylovorus dominant type (16.7%), which does not belong to conventional community state type (CST). Moreover, a minimal set of 33 bacterial species was identified to maximally differentiate CIN 2+ from CIN 1− in a random forest model, which can distinguish CIN 2+ from CIN 1− (area under the curve (AUC) = 0.952). Among the 33 bacterial species, Lactobacillus iners was selected as the most impactful predictor in our model. This finding suggests that the random forest model is able to predict the severity of CIN and vaginal microbiome may play a role as biomarker.