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Despite the benefits of quantitative data generated by massively parallel sequencing, resolving mitotypes from mixtures occurring in certain ratios remains challenging. In this study, a bioinformatic mixture deconvolution method centered on population-based phasing was developed and validated. The method was first tested on 270 in silico two-person mixtures varying in mixture proportions. An assortment of external reference panels containing information on haplotypic variation (from similar and different haplogroups) was leveraged to assess the effect of panel composition on phasing accuracy. Building on these simulations, mitochondrial genomes from the Human Mitochondrial DataBase were sourced to populate the panels and key parameter values were identified by deconvolving an additional 7290 in silico two-person mixtures. Finally, employing an optimized reference panel and phasing parameters, the approach was validated with in vitro two-person mixtures with differing proportions. Deconvolution was most accurate when the haplotypes in the mixture were similar to haplotypes present in the reference panel and when the mixture ratios were neither highly imbalanced nor subequal (e.g., 4:1). Overall, errors in haplotype estimation were largely bounded by the accuracy of the mixture’s genotype results. The proposed framework is the first available approach that automates the reconstruction of complete individual mitotypes from mixtures, even in ratios that have traditionally been considered problematic.

Unique molecular identifiers (UMIs) are a promising approach to contend with errors generated during PCR and massively parallel sequencing (MPS). With UMI technology, random molecular barcodes are ligated to template DNA molecules prior to PCR, allowing PCR and sequencing error to be tracked and corrected bioinformatically. UMIs have the potential to be particularly informative for the interpretation of short tandem repeats (STRs). Traditional MPS approaches may simply lead to the observation of alleles that are consistent with the hypotheses of stutter, while with UMIs stutter products bioinformatically may be re-associated with their parental alleles and subsequently removed. Herein, a bioinformatics pipeline named strumi is described that is designed for the analysis of STRs that are tagged with UMIs. Unlike other tools, strumi is an alignment-free machine learning driven algorithm that clusters individual MPS reads into UMI families, infers consensus super-reads that represent each family and provides an estimate the resulting haplotype's accuracy. Super-reads, in turn, approximate independent measurements not of the PCR products, but of the original template molecules, both in terms of quantity and sequence identity. Provisional assessments show that naive threshold-based approaches generate super-reads that are accurate (∼97 % haplotype accuracy, compared to ∼78 % when UMIs are not used), and the application of a more nuanced machine learning approach increases the accuracy to ∼99.5 % depending on the level of certainty desired. With these features, UMIs may greatly simplify probabilistic genotyping systems and reduce uncertainty. However, the ability to interpret alleles at trace levels also permits the interpretation, characterization and quantification of contamination as well as somatic variation (including somatic stutter), which may present newfound challenges.

Since 2013, STRait Razor has enabled analysis of massively parallel sequencing (MPS) data from various marker systems such as short tandem repeats, single nucleotide polymorphisms, insertion/deletions, and mitochondrial DNA. In this paper, STRait Razor Online (SRO), available at https://www.unthsc.edu/straitrazor, is introduced as an interactive, Shiny-based user interface for primary analysis of MPS data and secondary analysis of STRait Razor haplotype pileups. This software can be accessed from any common browser via desktop, tablet, or smartphone device. SRO is available also as a standalone application and open-source R script available at https://github.com/ExpectationsManaged/STRaitRazorOnline. The local application is capable of batch processing of both fastq files and primary analysis output. Processed batches generate individual report folders and summary reports at the locus- and haplotype-level in a matter of minutes. For example, the processing of data from ∼700 samples generated with the ForenSeq Signature Preparation Kit from allsequences.txt to a final table can be performed in ∼40 min whereas the Excel-based workbooks can take 35-60 h to compile a subset of the tables generated by SRO. To facilitate analysis of single-source, reference samples, a preliminary triaging system was implemented that calls potential alleles and flags loci suspected of severe heterozygote imbalance. When compared to published, manually curated data sets, 98.72 % of software-assigned allele calls without manual interpretation were consistent with curated data sets, 0.99 % loci were presented to the user for interpretation due to heterozygote imbalance, and the remaining 0.29 % of loci were inconsistent due to the analytical thresholds used across the studies.

The protozoan parasite Trypanosoma cruzi, the causative agent of Chagas disease, causes severe morbidity and mortality in afflicted individuals. About 30% of T. cruzi-infected individuals present with cardiac, gastrointestinal tract, and/or neurological disorders. Megacolon, one of the major pathologies of Chagas disease, is accompanied by gastrointestinal motility disorders. The molecular mechanism of T. cruzi-mediated megacolon in Chagas disease is currently unknown. To decipher the molecular mechanism of T. cruzi-induced alteration in the colon during the early infection phase, we exposed primary human colonic epithelial cells (HCoEpiC) to invasive T. cruzi trypomastigotes at multiple time points to determine changes in the phosphoprotein networks in the cells following infection using proteome profiler Human phospho-kinase arrays. We found significant changes in the phosphorylation pattern that can mediate cellular deregulations in colonic epithelial cells after infection. We detected a significant increase in the levels of phosphorylated heat shock protein (p-HSP) 27 and transcription factors that regulate various cellular functions, including c-Jun and CREB. Our study confirmed significant upregulation of phospho (p-) Akt S473, p-JNK, which may directly or indirectly modulate CREB and c-Jun phosphorylation, respectively. We also observed increased levels of phosphorylated CREB and c-Jun in the nucleus. Furthermore, we found that p-c-Jun and p-CREB co-localized in the nucleus at 180 minutes post infection, with a maximum Pearson correlation coefficient of 0.76±0.02. Increased p-c-Jun and p-CREB have been linked to inflammatory and profibrotic responses. T. cruzi infection of HCoEpiC induces an increased expression of thrombospondin-1 (TSP-1), which is fibrogenic at elevated levels. We also found that T. cruzi infection modulates the expression of NF-kB and JAK2-STAT1 signaling molecules which can increase pro-inflammatory flux. Bioinformatics analysis of the phosphoprotein networks derived using the phospho-protein data serves as a blueprint for T. cruzi-mediated cellular transformation of primary human colonic cells during the early phase of T. cruzi infection., Author summary Trypanosoma cruzi is a hemoflagellate that is now considered a global health threat in all industrialized regions of the world. Some chagasic patients present with digestive, neurological, and/or cardiac disorders. The mechanisms of T. cruzi-induced pathology remain to be elucidated. In this study, we challenged primary human colonic epithelial cells with T. cruzi and evaluated changes in the phosphorylated kinases and phosphoprotein levels that may induce cellular and molecular alterations leading to cellular transformations during the early phase of infection. The parasite induced significant increases in levels of phosphorylated kinases and phosphoproteins that govern multiple cellular pathways associated with immunological, stress, neuronal, and intercellular interactions as well as fibrogenic responses. The parasite also enhanced the levels of p-AKT, p-HSP27, p-JNK, and downstream transcription factors like p-c-Jun and p-CREB during the early infection phase. Additionally, we observed that the phosphorylated transcription factors are translocated to and colocalized in the nucleus in a time-dependent manner. These transcription factors regulate the expression of genes, including genes encoding extracellular matrix proteins, which play a role in the onset of colon pathology observed in some chagasic patients. Our study provides novel insights into the interactome that occurs during acute phase of T. cruzi infection of primary human colon cells.

Acinetobacter baumannii multidrug-resistant strain MMC4 was isolated from a bronchoalveolar lavage fluid sample from a patient in Nashville, TN, USA. Here, we report a draft genome sequence with a size of 3,985,367 bp, an average G+C content of 39.8%, and 3,863 predicted protein-coding sequences.