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This protocol describes a stepwise process to identify proteins of interest from a query proteome derived from NGS data. We implemented this protocol on Moringa oleifera transcriptome to identify proteins involved in secondary metabolite and vitamin biosynthesis and ion transport. This knowledge-driven protocol identifies proteins using an integrated approach involving sensitive sequence search and evolutionary relationships. We make use of functionally important residues (FIR) specific for the query protein family identified through its homologous sequences and literature. We screen protein hits based on the clustering with true homologues through phylogenetic tree reconstruction complemented with the FIR mapping. The protocol was validated for the protein hits through qRT-PCR and transcriptome quantification. Our protocol demonstrated a higher specificity as compared to other methods, particularly in distinguishing cross-family hits. This protocol was effective in transcriptome data analysis of M. oleifera as described in Pasha et al. Knowledge-driven protocol to identify secondary metabolite synthesizing protein in a highly specific manner. Use of functionally important residues for screening of true hits. Beneficial for metabolite pathway reconstruction in any (species, metagenomics) NGS data.

BackgroundAfrica has one of the highest incidences of gonorrhea. Neisseria gonorrhoeae is gaining resistance to most of the available antibiotics, compromising treatment across the world. Whole-genome sequencing (WGS) is an efficient way of predicting AMR determinants and their spread in the population. Recent advances in next-generation sequencing technologies like Oxford Nanopore Technology (ONT) have helped in the generation of longer reads of DNA in a shorter duration with lower cost. Increasing accuracy of base-calling algorithms, high throughput, error-correction strategies, and ease of using the mobile sequencer MinION in remote areas lead to its adoption for routine microbial genome sequencing. To investigate whether MinION-only sequencing is sufficient for WGS and downstream analysis in resource-limited settings, we sequenced the genomes of 14 suspected N. gonorrhoeae isolates from Nairobi, Kenya.MethodsUsing WGS, the isolates were confirmed to be cases of N. gonorrhoeae (n = 9), and there were three co-occurrences of N. gonorrhoeae with Moraxella osloensis and N. meningitidis (n = 2). N. meningitidis has been implicated in sexually transmitted infections in recent years. The near-complete N. gonorrhoeae genomes (n = 10) were analyzed further for mutations/factors causing AMR using an in-house database of mutations curated from the literature.ResultsWe observe that ciprofloxacin resistance is associated with multiple mutations in both gyrA and parC. Mutations conferring tetracycline (rpsJ) and sulfonamide (folP) resistance and plasmids encoding beta-lactamase were seen in all the strains, and tet(M)-containing plasmids were identified in nine strains. Phylogenetic analysis clustered the 10 isolates into clades containing previously sequenced genomes from Kenya and countries across the world. Based on homology modeling of AMR targets, we see that the mutations in GyrA and ParC disrupt the hydrogen bonding with quinolone drugs and mutations in FolP may affect interaction with the antibiotic.ConclusionHere, we demonstrate the utility of mobile DNA sequencing technology in producing a consensus genome for sequence typing and detection of genetic determinants of AMR. The workflow followed in the study, including AMR mutation dataset creation and the genome identification, assembly, and analysis, can be used for any clinical isolate. Further studies are required to determine the utility of real-time sequencing in outbreak investigations, diagnosis, and management of infections, especially in resource-limited settings.

Myosins are actin-based motor proteins involved in many cellular movements. It is interesting to study the evolutionary patterns and the functional attributes of various types of myosins. Computational search algorithms were performed to identify putative myosin members by phylogenetic analysis, sequence motifs, and coexisting domains. This study is aimed at understanding the distribution and the likely biological functions of myosins encoded in various taxa and available eukaryotic genomes. We report here a phylogenetic analysis of around 4,064 myosin motor domains, built entirely from complete or near-complete myosin repertoires incorporating many unclassified, uncharacterized sequences and new myosin classes, with emphasis on myosins from Fungi, Haptophyta, and other Stramenopiles, Alveolates, and Rhizaria (SAR). The identification of large classes of myosins in Oomycetes, Cellular slime molds, Choanoflagellates, Pelagophytes, Eustigmatophyceae, Fonticula, Eucoccidiorida, and Apicomplexans with novel myosin motif variants that are conserved and thus presumably functional extends our knowledge of this important family of motor proteins. This work provides insights into the distribution and probable function of myosins including newly identified myosin classes.