bioRxiv Science⌕ Search

Biology subjects

Hendricks, A.

Publications and source records attributed to Hendricks, A..

3 recordsLinked to original sources

The bacterial microbiome in Spider and Deathwatch beetles

The beetle family Ptinidae contains a number of economically important pests, such as the Cigarette beetle Lasioderma serricorne, the Drugstore beetle Stegobium paniceum, and the diverse Spider beetles. Many of these species are stored product pests which target a diverse range of food sources from dried tobacco to books made with organic materials. Despite the threat that the 2,200 species of Ptinidae beetles pose, fewer than 50 have been surveyed for microbial symbionts, and only a handful have been screened using contemporary genomic methods. In this study, we screen 116 individual specimens that cover most subfamilies of Ptinidae, with outgroup beetles from closely related families Dermestidae, Endecatomidae, and Bostrichidae. We used 16S ribosomal RNA gene amplicon data to characterize the bacterial microbiomes of these specimens. The majority of these species had never been screened for microbes. We found that, unlike in their sister family Bostrichidae that has two mutualistic bacteria seen in most species, there are no consistent bacterial members of ptinid microbiomes. For specimens which had Wolbachia infections, we did additional screening using multilocus sequence typing, and showed that our populations have different strains of Wolbachia than has been noted in previous publications. ImportancePtinid beetles are both household pests of pantry goods and economic pests of dried good warehouses and cultural archives such as libraries and museums. Currently, the most common pest control measures for ptinid beetles are phosphine and/or heat treatments. Many ptinid beetles have been observed to have increasing resistance to phosphine, and heat treatments are not appropriate for many of the goods commonly infested by ptinids. Pest control techniques focused on symbiotic bacteria have been shown to significantly decrease populations, and often have the beneficial side effect of being more specific than other pest control techniques. This survey provides foundational information about the bacteria associated with diverse ptinid species, which may be used for future control efforts.

microbiology↗

SimMiL: Simulating Microbiome Longitudinal Data

0.Structured AbstractO_ST_ABSMotivationC_ST_ABSThe quantity of statistical tools designed for omics data analysis has grown rapidly with the ability to collect large sets of human health data, particularly longitudinal data sets. Most tools are assessed for performance using simulated datasets constructed to mimic a handful of relevant characteristics from real world data sets. Consequently, the simulated data sets, and their respective simulation frameworks, are too narrow in scope to qualify as a standard for assessment in longitudinal omics analyses. ResultsHere we present the flexible and accessible simulation framework and software package called SimMiL (Simulating Microbiome Longitudinal data) capturing three general components of longitudinal microbiome data: (i) absence/presence of microbes, (ii) individual microbe abundance, and (iii) microbiome community composition over time. The framework is assessed by replicating the Type I error and Power analyses of a broad range of statistical tools (MirKAT, repeated measures permANOVA, and a modified kernel association test). Software AvaliabilityThe simulation framework is at https://github.com/nweaver111/SimMiL

bioinformatics↗

Cell Surface β-Lactamase Recruitment: A Facile Selection to Identify Protein-Protein Interactions

Protein-protein interactions are central to many cellular processes, and the identification of novel protein-protein interactions is a critical step in the discovery of protein therapeutics. Simple methods to identify naturally existing or laboratory evolved protein-protein interactions are therefore valuable research tools. We have developed a facile selection that links protein-protein interaction-dependent {beta}-lactamase recruitment on the surface of E. coli with resistance to ampicillin. Bacteria displaying a protein which form a complex with a specific protein-{beta}-lactamase fusion are protected from ampicillin-dependent cell death. In contrast, bacteria that do not recruit {beta}-lactamase to the cell surface are killed by ampicillin. Given its simplicity and tunability, we anticipate this selection will be a valuable addition to the palette of methods for illuminating and interrogating protein-protein interactions.

biochemistry↗