Biology subjects

Dimitrov, B.

Publications and source records attributed to Dimitrov, B..

9 recordsLinked to original sources

bioRxiv2025

Comparative analysis of plasma and bone marrow nutrient levels in pediatric B-ALL patients

Nutrient availability in the tumor microenvironment is a key determinant of cancer progression and therapeutic response, yet the physiological nutrient environment for most cancers is poorly understood. In this study, we investigated nutrient levels in pediatric B-cell acute lymphoblastic leukemia (B-ALL) patients across different subtypes undergoing chemotherapy, focusing on both bone marrow and circulation. Our analysis revealed distinct differences in nutrient profiles between leukemic and healthy plasma and among B-ALL subtypes, with hyperdiploid B-ALL exhibiting pronounced alterations in arginine and asymmetric dimethylarginine metabolism. Bone marrow and blood plasma exhibited largely similar metabolite profiles, even after chemotherapy, indicating these environments are metabolically comparable. Comparisons with renal cell carcinoma and non-small cell lung cancer highlighted a unique enrichment of tricarboxylic acid cycle intermediates in the circulation of B-ALL patients. These findings provide a comprehensive view of nutrient dynamics in pediatric B-ALL and identify metabolic alterations that could guide biomarker discovery and new therapeutic strategies.

cancer biology↗

bioRxiv2022

MIDAS2: Metagenomic Intra-species Diversity Analysis System

SummaryThe Metagenomic Intra-Species Diversity Analysis System (MIDAS) is a scalable metagenomic pipeline that identifies single nucleotide variants (SNVs) and gene copy number variants (CNVs) in microbial populations. Here, we present MIDAS2, which addresses the computational challenges presented by increasingly large reference genome databases, while adding functionality for building custom databases and leveraging paired-end reads to improve SNV accuracy. This fast and scalable reengineering of the MIDAS pipeline enables thousands of metagenomic samples to be efficiently genotyped. Availability and ImplementationThe source code is available at https://github.com/czbiohub/MIDAS2. The documentation is available at https://midas2.readthedocs.io/en/latest/. Supplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2020

Ultra-rapid metagenotyping of the human gut microbiome

Sequence variation is used to quantify population structure and identify genetic determinants of phenotypes that vary within species. In the human microbiome and other environments, single nucleotide polymorphisms (SNPs) are frequently detected by aligning metagenomic sequencing reads to catalogs of genes or genomes. But this requires high-performance computing and enough read coverage to distinguish SNPs from sequencing errors. We solved these problems by developing the GenoTyper for Prokaytotes (GT-Pro), a suite of novel methods to catalog SNPs from genomes and use exact k-mer matches to perform ultra-fast reference-based SNP calling from metagenomes. Compared to read alignment, GT-Pro is more accurate and two orders of magnitude faster. We discovered 104 million SNPs in 909 human gut species, characterized their global population structure, and tracked pathogenic strains. GT-Pro democratizes strain-level microbiome analysis by making it possible to genotype hundreds of metagenomes on a personal computer. Software availabilityGT-Pro is available at https://github.com/zjshi/gt-pro.

bioinformatics↗

bioRxiv2020

IDseq - An Open Source Cloud-based Pipeline and Analysis Service for Metagenomic Pathogen Detection and Monitoring

BackgroundMetagenomic next generation sequencing (mNGS) has enabled the rapid, unbiased detection and identification of microbes without pathogen-specific reagents, culturing, or a priori knowledge of the microbial landscape. mNGS data analysis requires a series of computationally intensive processing steps to accurately determine the microbial composition of a sample. Existing mNGS data analysis tools typically require bioinformatics expertise and access to local server-class hardware resources. For many research laboratories, this presents an obstacle, especially in resource limited environments. FindingsWe present IDseq, an open source cloud-based metagenomics pipeline and service for global pathogen detection and monitoring (https://idseq.net). The IDseq Portal accepts raw mNGS data, performs host and quality filtration steps, then executes an assembly-based alignment pipeline which results in the assignment of reads and contigs to taxonomic categories. The taxonomic relative abundances are reported and visualized in an easy-to-use web application to facilitate data interpretation and hypothesis generation. Furthermore, IDseq supports environmental background model generation and automatic internal spike-in control recognition, providing statistics which are critical for data interpretation. IDseq was designed with the specific intent of detecting novel pathogens. Here, we benchmark novel virus detection capability using both synthetically evolved viral sequences, and real-world samples, including IDseq analysis of a nasopharyngeal swab sample acquired and processed locally in Cambodia from a tourist from Wuhan, China, infected with the recently emergent SARS-CoV-2. ConclusionThe IDseq Portal reduces the barrier to entry for mNGS data analysis and enables bench scientists, clinicians, and bioinformaticians to gain insight from mNGS datasets for both known and novel pathogens.

bioinformatics↗

bioRxiv2020

Crystal structure and interaction studies of human DHTKD1 provide insight into a mitochondrial megacomplex in lysine catabolism

DHTKD1 is a lesser-studied E1 enzyme belonging to the family of 2-oxoacid dehydrogenases. DHTKD1, in complex with the E2 (dihydrolipoamide succinyltransferase, DLST) and E3 (lipoamide dehydrogenase, DLD) components, is implicated in lysine and tryptophan catabolism by catalysing the oxidative decarboxylation of 2-oxoadipate (2OA) in the mitochondria. Here, we solved the crystal structure of human DHTKD1 at 1.9 [A] resolution in binary complex with the thiamine diphosphate (ThDP) cofactor. Our structure explains the evolutionary divergence of DHTKD1 from the well-characterized homologue 2-oxoglutarate (2OG) dehydrogenase, in its preference for the larger 2OA substrate than 2OG. Inherited DHTKD1 missense mutations cause the lysine metabolic condition 2-aminoadipic and 2-oxoadipic aciduria. Reconstruction of the missense variant proteins reveal their underlying molecular defects, which include protein destabilisation, disruption of protein-protein interactions, and alterations in the protein surface. We further generated a 5.0 [A] reconstruction of the human DLST inner core by single-particle electron microscopy, revealing a 24-mer cubic architecture that serves as a scaffold for assembly of DHTKD1 and DLD. This structural study provides a starting point to develop small molecule DHTKD1 inhibitors for probing mitochondrial energy metabolism.

biochemistry↗

bioRxiv2020

Designing and implementing programmable depletion in sequencing libraries with DASHit

Since Next-Generation Sequencing produces reads uniformly subsampled from an input library, highly abundant sequences may mask interesting low abundance sequences. The DASH (Depleting Abundant Sequences by Hybridization) technique takes advantage of the programmability of CRISPR/Cas9 to deplete unwanted high-abundance sequences. Because desired depletion targets vary by sample type, here we describe DASHit, software that outputs an optimal DASH target set given a sequencing dataset, an updated DASH protocol, and show depletion results with DASHit-designed targets for three different species.

microbiology↗

bioRxiv2019

Unbiased metagenomic sequencing for pediatric meningitis in Bangladesh reveals neuroinvasive Chikungunya virus outbreak and other unrealized pathogens

The disease burden due to meningitis in low and middle-income countries remains significant and failure to determine an etiology impedes appropriate treatment for patients and evidence-based policy decisions for populations. Broad-range pathogen surveillance using metagenomic next-generation sequencing (mNGS) of RNA isolated from cerebral spinal fluid (CSF) provides an unbiased assessment for possible infectious etiologies. In this study, our objective was to use mNGS to identify etiologies of pediatric meningitis in Bangladesh.\n\nWe conducted a retrospective case-control mNGS study on CSF from patients with known neurologic infections (n=36), idiopathic meningitis (n=25), without infection (n=30) and six environmental samples collected between 2012-2018. Using an open-access, cloud-based bioinformatics pipeline (IDseq) and machine learning, we identified potential pathogens which were confirmed through qPCR and Sanger sequencing. These cases were followed-up through phone/home-visits. The CSF samples were collected from children with WHO-defined meningeal signs during prospective meningitis surveillance at the largest pediatric referral hospital in Bangladesh.\n\nThe 91 participants (42% female) ranged in age from 0-160 months (median: 9 months). In samples with known infectious causes of meningitis and without infections (n=66), there was 83% concordance between mNGS and conventional testing. In idiopathic cases (n=25), mNGS identified a potential etiology in 40% (n=10), including bacterial and viral pathogens. There were three instances of neuroinvasive Chikungunya virus (CHIKV). The CHIKV genomes were >99% identical to each other and to a Bangladeshi strain only previously recognized to cause systemic illness in 2017. CHIKV qPCR of all remaining stored CSF samples from children who presented with idiopathic meningitis in 2017 at the same hospital (n=472) revealed 17 additional CHIKV meningitis cases. Orthogonal molecular confirmation of each mNGS-identified infection, case-based clinical data, and follow-up of patients substantiated the key findings.\n\nUsing mNGS, we obtained a microbiological diagnosis for 40% of idiopathic meningitis cases and identified a previous unappreciated pediatric CHIKV meningitis outbreak. Case-control CSF mNGS surveys can complement conventional diagnostic methods to identify etiologies of meningitis and facilitate informed policy decisions.

genomics↗

bioRxiv2018

FLASH: A next-generation CRISPR diagnostic for multiplexed detection of antimicrobial resistance sequences

The growing prevalence of deadly microbes with resistance to previously life-saving drug therapies is a dire threat to human health. Detection of low abundance pathogen sequences remains a challenge for metagenomic Next Generation Sequencing (NGS). We introduce FLASH (Finding Low Abundance Sequences by Hybridization), a next-generation CRISPR/Cas9 diagnostic method that takes advantage of the efficiency, specificity and flexibility of Cas9 to enrich for a programmed set of sequences. FLASH-NGS achieves up to 5 orders of magnitude of enrichment and sub-attomolar gene detection with minimal background. We provide an open-source software tool (FLASHit) for guide RNA design. Here we applied it to detection of antimicrobial resistance genes in respiratory fluid and dried blood spots, but FLASH-NGS is applicable to all areas that rely on multiplex PCR.

microbiology↗

bioRxiv2018

Etiology of fever in Ugandan children: identification of microbial pathogens using metagenomic next-generation sequencing and IDseq, a platform for unbiased metagenomic analysis

BackgroundFebrile illness is a major burden in African children, and non-malarial causes of fever are uncertain. We built and employed IDseq, a cloud-based, open access, bioinformatics platform and service to identify microbes from metagenomic next-generation sequencing of tissue samples. In this pilot study, we evaluated blood, nasopharyngeal, and stool specimens from 94 children (aged 2-54 months) with febrile illness admitted to Tororo District Hospital, Uganda.\n\nResultsThe most common pathogens identified were Plasmodium falciparum (51.1% of samples) and parvovirus B19 (4.4%) from blood; human rhinoviruses A and C (40%), respiratory syncytial virus (10%), and human herpesvirus 5 (10%) from nasopharyngeal swabs; and rotavirus A (50% of those with diarrhea) from stool. Among other potential pathogens, we identified one novel orthobunyavirus, tentatively named Nyangole virus, from the blood of a child diagnosed with malaria and pneumonia, and Bwamba orthobunyavirus in the nasopharynx of a child with rash and sepsis. We also identified two novel human rhinovirus C species.\n\nConclusionsThis exploratory pilot study demonstrates the utility of mNGS and the IDseq platform for defining the molecular landscape of febrile infectious diseases in resource limited areas. These methods, supported by a robust data analysis and sharing platform, offer a new tool for the surveillance, diagnosis, and ultimately treatment and prevention of infectious diseases.

genomics↗