Biology subjects

Carter, D. O.

Publications and source records attributed to Carter, D. O..

3 recordsLinked to original sources

bioRxiv2025

IDBac: an open-access web platform and compendium for the identification of bacteria by MALDI-TOF mass spectrometry.

The identification and analysis of bacteria is central to the microbiological sciences. While gene sequencing methods have been the standard to achieve this, use of MALDI-TOF mass spectrometry (MS), particularly in clinical microbiology, provides high-throughput identification to the subspecies level. However, biotyping has yet to be adopted outside of clinical settings due to the lack of a centralized public database of MS protein signatures that would facilitate isolate identification via spectral comparison. Further, current platforms lack meaningful ways to compare multiple properties from large numbers of bacterial isolates. Herein we present the IDBac web platform, a crowd-sourced central knowledgebase of protein MS signatures of >1400 strains spanning 6 bacterial phyla. Accompanying the knowledgebase is analysis infrastructure to identify unknown isolates, probe relationships within culture collections using metadata integration, and visualize specialized metabolite differences within groups of closely related bacteria. To highlight this utility and encourage wide community contribution, examples of each are presented.

microbiology↗

bioRxiv2020

The Effects of Inter-Individual Biological Differences and Taphonomic Alteration on Human Bone Protein Profiles: Implications for the Development of PMI/AAD Estimation Methods

Bone proteomics studies using animal proxies and skeletonized human remains have delivered encouraging results in the search for potential biomarkers for precise and accurate post-mortem interval (PMI) and the age-at-death (AAD) estimation in medico-legal investigations. At present, however, the effects of inter-individual biological differences and taphonomic alteration on recovered human bone protein profiles are not well understood. This study investigated the human bone proteome in four human body donors studied throughout decomposition outdoors. The effects of ageing phenomena (in vivo and post-mortem), and intrinsic and extrinsic variables on the variety and abundancy of the bone proteome were assessed. Results identified a new potential biomarker for PMI estimation, as well as three potential biomarkers for AAD estimation. The results also suggest that bone mineral density (BMD) may be an important variable affecting the survival and extraction of proteins. Highlights- CO3, CO9, COBA2, CO3A1, MGP, PGS2 and TTHY are potential biomarkers for post-mortem interval estimation in skeletonized human remains - FETUA, ALBU and OLFL3 are potential biomarkers for age-at-death estimation in human remains - Taphonomic and biological variables play a significant role in survival and extraction rates of proteins in bone - Bone mineral density may affect survival of proteins in bone, probably due to the effects of the mineral matrix on the movement of decomposer microbes - Higher bone mineral density may affect the survival and the extraction rate of collagen and mineral-binding proteins

biochemistry↗

bioRxiv2019

Patterns of microbial colonization of human bone from surface-decomposed remains

Microbial colonization of bone is an important mechanism of post-mortem skeletal degradation. However, the types and distributions of bone and tooth colonizing microbes are not well characterized. It is unknown if microbial communities vary in abundance or composition between bone element types, which could help explain patterns of human DNA preservation. The goals of the present study were to (1) identify the types of microbes capable of colonizing different human bone types and (2) relate microbial abundances, diversity, and community composition to bone type and human DNA preservation. DNA extracts from 165 bone and tooth samples from three skeletonized individuals were assessed for bacterial loading and microbial community composition and structure. Random forest models were applied to predict operational taxonomic units (OTUs) associated with human DNA concentration. Dominant bacterial bone colonizers were from the phyla Proteobacteria (36%), Actinobacteria (23%), Firmicutes (13%), Bacteroidetes (12%), and Planctomycetes (4.4%). Eukaryotic bone colonizers were from Ascomycota (40%), Apicomplexa (21%), Annelida (19%), Basidiomycota (17%), and Ciliophora (14%). Bacterial loading was not a significant predictor of human DNA concentration in two out of three individuals. Random forest models were minimally successful in identifying microbes related to patterns of DNA preservation, complicated by high variability in community structure between individuals and body regions. This work expands on our understanding of the types of microbes capable of colonizing human bone and contributing to human skeletal DNA degradation.

microbiology↗