Skin microbiota diversity among genetically unrelated individuals of Indian origin
Background Human skin harbors complex transient and resident microbial communities that show intra- & inter-individual variation due to various environmental and host-associated factors such as skin site, diet, age, gender, genetics, or the type and use of cosmetics. This variation remains largely uncharacterized in the Indian population; hence, the present study aims to characterize the variation in skin microbiota among individuals of Indian origin and quantify associations with age, diet, and geography. Methods Axillary sweat samples from genetically unrelated individuals (N = 58) residing in the three geographical locations of Maharashtra, India, were collected using a sterile cotton swab. Bacterial DNA was extracted using a standard protocol and checked for quality. Variable regions (V3–V4) of the 16S rRNA gene were sequenced using the Illumina platform. We used standard methods from microbiota bioinformatics, including alpha and beta diversity, community typing, and differential abundance, to quantify the association of skin microbiota with age, diet, and geographical location. Results Our study indicated the prevalence of phyla- Firmicutes, Proteobacteria, and Actinobacteria, consistent with previous reports on skin microbiota composition of the world population level. The alpha diversity (Shannon index) was significantly associated with the age group (Kruskal–Wallis test, p = 0.02), but not with geography (p = 0.62) or diet (p = 0.74). The overall skin microbiota community composition was significantly associated with geographical location based on Community State Types (CST) analysis and PERMANOVA (R2 = 0.07, p = 0.01). Differential abundance analysis at the genus level indicated a distinctively high abundance of Staphylococcus and Corynebacterium among individuals of the Pune district. Pseudomonas and Anaerococcus were abundant in individuals from Ahmednagar whereas, Paenibacillus, Geobacillus, Virgibacillus, Jeotgalicoccus, Pullulanibacillus, Delsulfosporomusa, Citinovibrio, and Calditerricola were abundant in individuals from Nashik district. Conclusion Our work provides one of the first characterizations of skin microbiota variation in different sub-populations in India. The analysis quantifies the level of individuality, as contrasted to the other factors of age, geography, and diet, thus helping to evaluate the applicability of skin microbiota profiles as a potential biomarker to stratify individuals.
Potbhare et al. (2022) Skin microbiota diversity among genetically unrelated individuals of Indian origin. PeerJ 10:e13075 https://doi.org/10.7717/peerj.13075
Whole-genome analysis of CGS, SAHH, SAMS gene families in five Rosaceae species and their expression analysis in Pyrus bretschneideri
Cystathionine γ-synthase (CGS), S-adenosyl-L-homocysteine hydrolase (SAHH), and S-adenosy-L-methionine synthetase (SAMS) play an important role in the regulation of plant growth, development, and secondary metabolism. In this study, a total of 6 CGS, 6 SAHH, and 28 SAMS genes were identified from five Rosaceae species (Pyrus bretschneideri, Prunus persica, Prunus mume, Fragaria vesca, and Malus domestica). The evolutionary relationship and microsynteny analysis in five Rosaceae species revealed that duplicated regions were conserved between three gene families (CGS, SAHH, SAMS). Moreover, the chromosomal locations, gene structures, conserved motifs, cis-elements, physicochemical properties, and Ka/Ks analysis were performed by using numerous bioinformatics tools. The expression of different organs showed that the CGS, SAHH and SAMS genes of pear have relatively high expression patterns in flowers and stems, except for PbCGS1. RNA-seq and qRT-PCR combined analysis showed that PbSAMS1 may be involved in the regulation of pear stone cell development. In summary, this study provides the basic information of CGS, SAHH and SAMS genes in five Rosaceae species, further revealing the expression patterns in the pear fruit, which provides the theoretical basis for the regulation of pear stone cells.
Zhang et al. (2022) Whole-genome analysis of CGS, SAHH, SAMS gene families in five Rosaceae species and their expression analysis in Pyrus bretschneideri. PeerJ 10:e13086 https://doi.org/10.7717/peerj.13086
Identification of potential biomarkers of vascular calcification using bioinformatics analysis and validation in vivo
Background Vascular calcification (VC) is the most widespread pathological change in diseases of the vascular system. However, we know poorly about the molecular mechanisms and effective therapeutic approaches of VC. Methods The VC dataset, GSE146638, was downloaded from the Gene Expression Omnibus (GEO) database. Using the edgeR package to screen Differentially expressed genes (DEGs). Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to find pathways affecting VC. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on the DEGs. Meanwhile, using the String database and Cytoscape software to construct protein-protein interaction (PPI) networks and identify hub genes with the highest module scores. Correlation analysis was performed for hub genes. Receiver operating characteristic (ROC) curves, expression level analysis, GSEA, and subcellular localization were performed for each hub gene. Expression of hub genes in normal and calcified vascular tissues was verified by quantitative reverse transcription PCR (RT-qPCR) and immunohistochemistry (IHC) experiments. The hub gene-related miRNA-mRNA and TF-mRNA networks were constructed and functionally enriched for analysis. Finally, the DGIdb database was utilized to search for alternative drugs targeting VC hub genes. Results By comparing the genes with normal vessels, there were 64 DEGs in mildly calcified vessels and 650 DEGs in severely calcified vessels. Spp1, Sost, Col1a1, Fn1, and Ibsp were central in the progression of the entire VC by the MCODE plug-in. These hub genes are primarily enriched in ossification, extracellular matrix, and ECM-receptor interactions. Expression level results showed that Spp1, Sost, Ibsp, and Fn1 were significantly highly expressed in VC, and Col1a1 was incredibly low. RT-qPCR and IHC validation results were consistent with bioinformatic analysis. We found multiple pathways of hub genes acting in VC and identified 16 targeting drugs. Conclusions This study perfected the molecular regulatory mechanism of VC. Our results indicated that Spp1, Sost, Col1a1, Fn1, and Ibsp could be potential novel biomarkers for VC and promising therapeutic targets.
Chen et al. (2022) Identification of potential biomarkers of vascular calcification using bioinformatics analysis and validation in vivo. PeerJ 10:e13138 https://doi.org/10.7717/peerj.13138
Study on the differences of phyllosphere microorganisms between poplar hybrid offspring and their parents
The females and males of dioecious plants have evolved sex-specific characteristics in terms of their morphological and physiological properties. However, the differentiation of phyllosphere microorganism of dioecious plants between parents and hybrid offspring remain largely unexplored. Here, the phyllosphere bacterial and fungal community diversity and composition of female (Populus nigra ‘DH5’ (PNDH5)), male (P. simonii ‘DH4’ (PSDH4)), and the hybrid offspring (P. simonii × P. nigra ‘DH1’ (PSPNDH1), P. simonii × P. nigra ‘DH2’ (PSPNDH2), P. simonii × P. nigra ‘DH3’ (PSPNDH3)) were investigated using 16S rDNA/ITS rDNA gene-based Illumina NovaSeq 6000 sequencing. There was considerable variation of plant height, diameter at breast height, leaf area, length of petioles, leaf moisture content, and starch among different samples, and PSDH2 owned the highest plant height, diameter at breast height, and length of petioles. No distinct differences of phyllosphere bacterial community diversity were observed among PSDH4, PNDH5, PSPNDH1, PSPNDH2, and PSPNDH3; while, PSPNDH2 owned the highest fungal Pielou_e index, Shannon index, and Simpson index. Firmicutes and Ascomycota were the predominant phyllosphere bacterial and fungal community at the phylum level, respectively. Bacilli and Gammaproteobacteria were the two most dominant bacterial classes regardless of parent and the hybrid offspring. The predominant phyllosphere fungal community was Dothideomycetes at the class level. The NMDS demonstrated that phyllosphere microbial community obviously differed between parents and offspring, while the phyllosphere microbial community presented some similarities under different hybrid progeny. Also, leaf characteristics contributed to the differentiation of phyllosphere bacterial and fungal communities between parents and hybrid offspring. These results highlighted the discrimination of phyllosphere microorganisms on parent and hybrid offspring, which provided clues to potential host-related species in the phyllosphere environment.
Ding et al. (2022) Study on the differences of phyllosphere microorganisms between poplar hybrid offspring and their parents. PeerJ 10:e12915 https://doi.org/10.7717/peerj.12915
CIAlign: A highly customisable command line tool to clean, interpret and visualise multiple sequence alignments
Background Throughout biology, multiple sequence alignments (MSAs) form the basis of much investigation into biological features and relationships. These alignments are at the heart of many bioinformatics analyses. However, sequences in MSAs are often incomplete or very divergent, which can lead to poor alignment and large gaps. This slows down computation and can impact conclusions without being biologically relevant. Cleaning the alignment by removing common issues such as gaps, divergent sequences, large insertions and deletions and poorly aligned sequence ends can substantially improve analyses. Manual editing of MSAs is very widespread but is time-consuming and difficult to reproduce. Results We present a comprehensive, user-friendly MSA trimming tool with multiple visualisation options. Our highly customisable command line tool aims to give intervention power to the user by offering various options, and outputs graphical representations of the alignment before and after processing to give the user a clear overview of what has been removed. The main functionalities of the tool include removing regions of low coverage due to insertions, removing gaps, cropping poorly aligned sequence ends and removing sequences that are too divergent or too short. The thresholds for each function can be specified by the user and parameters can be adjusted to each individual MSA. CIAlign is designed with an emphasis on solving specific and common alignment problems and on providing transparency to the user. Conclusion CIAlign effectively removes problematic regions and sequences from MSAs and provides novel visualisation options. This tool can be used to fine-tune alignments for further analysis and processing. The tool is aimed at anyone who wishes to automatically clean up parts of an MSA and those requiring a new, accessible way of visualising large MSAs.
Tumescheit et al. (2022) CIAlign: A highly customisable command line tool to clean, interpret and visualise multiple sequence alignments. PeerJ 10:e12983 https://doi.org/10.7717/peerj.12983
Diegoaelurus, a new machaeroidine (Oxyaenidae) from the Santiago Formation (late Uintan) of southern California and the relationships of Machaeroidinae, the oldest group of sabertooth mammals
Machaeroidinae is a taxonomically small clade of early and middle Eocene carnivorous mammals that includes the earliest known saber-toothed mammalian carnivores. Machaeroidine diversity is low, with only a handful of species described from North America and Asia. Here we report a new genus and species of machaeroidine, Diegoaelurus vanvalkenburghae, established on the basis of a nearly complete dentary with most of the dentition from the late Uintan (middle Eocene) portion of the Santiago Formation of southern California. The new taxon is the youngest known machaeroidine and provides the first evidence for the presence of multiple machaeroidine lineages, as it differs substantially from Apataelurus kayi, the only near-contemporaneous member of the group. Phylogenetic analysis indicates that Diegoaelurus is the sister taxon of Apataelurus, while older species are recovered as a monophyletic Machaeroides. Both phylogenetic results are relatively weakly supported. The new taxon extends the record of machaeroidines to the end of the Uintan, potentially tying machaeroidine extinction to the faunal turnover spanning the middle to late Eocene transition in North America.
Zack et al. (2022) Diegoaelurus, a new machaeroidine (Oxyaenidae) from the Santiago Formation (late Uintan) of southern California and the relationships of Machaeroidinae, the oldest group of sabertooth mammals. PeerJ 10:e13032 https://doi.org/10.7717/peerj.13032
Spinal-pelvic sagittal parameters in patients with gluteal muscle contracture: an imaging study
Background Gluteal muscle contracture (GMC) may cause abnormal spinal alignment as well as hip and pelvic deformities. The spine-pelvis alignment of GMC patients is unclear. This study aimed to describe the spine-pelvis sagittal alignment in patients with GMC and to explore the impact of GMC on the pathogenesis of low back pain (LBP). Methods Radiological analysis was performed in 100 patients with GMC and 100 asymptomatic volunteers who acted as the control group. Sagittal parameters were measured by two independent raters and their averages were presented on lateral radiographs of the whole spine, including pelvic incidence (PI), sagittal vertical axis (SVA), pelvic tilt (PT), lumbar lordosis (LL), sacral slope (SS), thoracic kyphosis (TK), and the relationship between PI and LL (expressed as PI-LL). All cases were categorized into one of three classes based on the apex position of lumbar lordosis and were further divided into three groups by the PI value. The GMC and control parameters were compared and the correlations between the parameters in the GMC group were analysed. Results The PI value of the GMC group was significantly less than that of the control group (42.38 ± 10.90° vs 45.68 ± 7.49°, P < 0.05). There was no difference found between the key parameters (SVA, PT, and PI-LL), which correlated with outcomes in adult deformity. No differences of SS were found between the two groups (P > 0.05). The GMC group showed lower average LL (42.77 ± 10.97° vs 46.41 ± 9.07°) and TK (17.34 ± 9.50° vs 20.45 ± 8.02°) compared with the control group (P < 0.05). LL was correlated with PI, SS, PT, TK (P < 0.01) and SVA (P < 0.05). TK and SVA were not correlated with any parameters except LL and pairwise correlations were found among PI, SS, and PT. There were no differences found between the distributions of the lumbar lordosis apex of GMC and the control but the range of SS in apex groups 3 and 4 did differ. GMC patients had the most small-PI value (44%) while approximately 64% of asymptomatic individuals had a normal PI. Interobserver variability was sufficient for all parameters calculated by the intraclass correlation coefficient (ICC). Conclusions Gluteal muscle contracture causes a low PI which may contribute to low back pain. Patients with GMC present the same global sagittal spinal-pelvic balance as asymptomatic individuals due to a compensatory mechanism through excessive flat lumbar and thoracic curves. Future studies on the relationship between spinal-pelvic sagittal and coronal alignment and low back pain are needed to understand the mechanical forces involved in the onset of GMC.
Liu et al. (2022) Spinal-pelvic sagittal parameters in patients with gluteal muscle contracture: an imaging study. PeerJ 10:e13093 https://doi.org/10.7717/peerj.13093
Freeze-drying can replace cold-chains for transport and storage of fecal microbiome samples
Background The transport and storage of samples in temperatures of minus 80 °C is commonly considered as the gold standard for microbiome studies. However, studies conducting sample collection at remote sites without a reliable cold-chain would benefit from a sample preservation method that allows transport and storage at ambient temperature. Methods In this study we compare alpha diversity and 16S microbiome composition of 20 fecal sample replicates from Damaraland mole-rats (Fukomys damarensis) preserved in a minus 80 °C freezer and transported on dry ice to freeze-dried samples that were stored and transported in ambient temperature until DNA extraction. Results We found strong correlations between relative abundances of Amplicon Sequence Variants (ASVs) between preservation treatments of the sample, no differences in alpha diversity measures between the two preservation treatments and minor effects of the preservation treatment on beta diversity measures. Our results show that freeze-drying samples can be a useful method for cost-effective transportation and storage of microbiome samples that yields quantitatively almost indistinguishable results in 16S microbiome analyses as those stored in minus 80 °C.
Bensch et al. (2022) Freeze-drying can replace cold-chains for transport and storage of fecal microbiome samples. PeerJ 10:e13095 https://doi.org/10.7717/peerj.13095
Predicting population: development and validation of a new predictive nomogram for evaluating medication nonadherence risk in a type 2 diabetes
Background Diabetes mellitus is a growing global health challenge and affects patients of all ages. Treatment aims to keep blood glucose levels close to normal and to prevent or delay complications. However, adherence to antidiabetic medicines is often unsatisfactory. Purpose Here, we established and internally validated a medication nonadherence risk nomogram for use in Chinese type 2 diabetes mellitus (T2DM) patients. Methods This cross-sectional study was carried out from July–December 2020 on randomly selected T2DM patients visiting a diabetes clinic and included 753 participants. Adherence was analyzed based on an eight-item Morisky Medication Adherence Scale (MMAS-8). Other data, including patient demographics, treatment, complications, and comorbidities, were also collected on questionnaires. Optimization of feature selection to develop the medication nonadherence risk model was achieved using the least absolute shrinkage and selection operator regression model (LASSO). A prediction model comprising features selected from LASSO model was designed by applying multivariable logistic regression analysis. The decision curve analysis, calibration plot, and C-index were utilized to assess the performance of the model in terms of discrimination, calibration, and clinical usefulness. Bootstrapping validation was applied for internal validation. Results The prediction nomogram comprised several factors including sex, marital status, education level, employment, distance, self-monitoringofbloodglucose, disease duration, and dosing frequency of daily hypoglycemics (pills, insulin, or glucagon-like peptide-1). The model exhibited good calibration and good discrimination (C-index = 0.79, 95% CI [0.75–0.83]). In the validation samples, a high C-index (0.75) was achieved. Results of the decision curve analysis revealed that the nonadherence nomogram could be applied in clinical practice in cases where the intervention is decided at a nonadherence possibility threshold of 12%. Conclusion The number of patients who adhere to anti-diabetes therapy was small. Being single male, having no formal education, employed, far from hospital, long disease duration, and taking antidiabetics twice or thrice daily, had significant negative correlation with medication adherence. Thus, strategies for improving adherence are urgently needed.
QiMuge et al. (2022) Predicting population: development and validation of a new predictive nomogram for evaluating medication nonadherence risk in a type 2 diabetes. PeerJ 10:e13102 https://doi.org/10.7717/peerj.13102
Biochemical analysis of collagens from the bone of lizardfish (Saurida tumbil Bloch, 1795) extracted with different acids
Background Lizardfish (Saurida tumbil Bloch, 1795) bone is a fish by-product generated during industrial surimi processing. This by-product is an important source of collagen production since the use of terrestrial animal-based collagens no longer sought due to concern regarding the transfer of infectious diseases and religious issues. Hence, this study was carried out to determine the biochemical analysis of collagens from the bone of lizardfish extracted with different acids. Methods Lizardfish bone collagens were extracted with various acids (i.e., acetic, lactic and citric acids). All extraction processes were conducted in a chiller room (4 °C). The extracted collagens were biochemically characterized, such as hydroxyproline content, Ultraviolet (UV) absorption, X-ray diffraction (XRD), Fourier transform infrared spectroscopy spectra (FTIR), Differential scanning calorimetry (DSC) and solubility in different pH values and NaCl concentrations. Results The yield of extracted collagens ranged between 1.73% and 2.59%, with the highest (p < 0.05) observed in citric acid-extracted collagen (CaEC). Protein patterns confirmed that all-collagen samples had two identical subunits, α1 and α2, representing type I collagen. The highest whiteness value was found in acetic acid-extracted collagen (AaEC), but there was no significant difference (p ≥ 0.05) compared to lactic acid-extracted collagen (LaEC). UV absorption and XRD analysis reflected the characteristics of the collagen, as reported in the literature. For the FTIR, all acid-extracted collagen samples presented a triple helical structure. The thermal transition temperature (Tmax = 77.92–89.04 °C) was in accordance with collagen extracted from other fish species. All extracted collagens were highly soluble in acidic pH and low concentrations of NaCl (0–20 g/L). In conclusion, collagens extracted from lizardfish bone may be used as alternative sources of collagen in industrial settings, and AaEC would be considered superior in terms of the characteristics evaluated in this study.
Jaziri et al. (2022) Biochemical analysis of collagens from the bone of lizardfish (Saurida tumbil Bloch, 1795) extracted with different acids. PeerJ 10:e13103 https://doi.org/10.7717/peerj.13103