Genetic analysis of the Drosophila ellipsoid body neuropil: Organization and development of the central complex

The central complex is an important center for higher‐order brain function in insects. It is an intricate neuropil composed of four substructures. Each substructure contains repeated neuronal elements which are connected by processes such that topography is maintained. Although the neuronal architecture has been described in several insects and the behavioral role investigated in various experiments, the exact function of this neuropil has proven elusive. To describe the architecture of the central complex, we study 15 enhancer‐trap lines that label various ellipsoid body neuron types. We find evidence for restriction of gene expression that is correlated with specific neuronal types: such correlations suggest functional classifications as well. We show that some enhancer‐trap patterns reveal a single ellipsoid body neuron type, while others label multiple types. We describe the development of the ellipsoid body neuropil in wild‐type animals and propose developmental mechanisms based on animals displaying structural mutations of this neuropil. The experiments performed here demonstrate the degree of resolution possible from the analysis of enhancer‐trap lines and form a useful library of tools for future structure/function studies of the ellipsoid body. © 1999 John Wiley & Sons, Inc. J Neurobiol 41: 189–207, 1999     

Bioinspiration as a method of problem‐based STEM education: A case study with a class structured around the COVID‐19 crisis

Bioinspiration is a promising lens for biology instruction as it allows the instructor to focus on current issues, such as the COVID‐19 pandemic. From social distancing to oxygen stress, organisms have been tackling pandemic‐related problems for millions of years. What can we learn from such diverse adaptations in our own applications? This review uses a seminar course on the COVID‐19 crisis to illustrate bioinspiration as an approach to teaching biology content. At the start of the class, students mind‐mapped the entire problem; this range of subproblems was used to structure the biology content throughout the entire class. Students came to individual classes with a brainstormed list of biological systems that could serve as inspiration for a particular problem (e.g., absorptive leaves in response to the problem of toilet paper shortages). After exploration of relevant biology content, discussion returned to the focal problem. Students dug deeper into the literature in a group project on mask design and biological systems relevant to filtration and transparency. This class structure was an engaging way for students to learn principles from ecology, evolution, behavior, and physiology. Challenges with this course design revolved around the interdisciplinary and creative nature of the structure; for instance, the knowledge of the participants was often stretched by engineering details. While the present class was focused on the COVID‐19 crisis, a course structured through a bioinspired approach can be applied to other focal problems, or subject areas, giving instructors a powerful method to deliver interdisciplinary content in an integrated and inquiry‐driven way.     

Detecting and accounting for multiple sources of positional variance in peak list registration analysis and spin system grouping

Peak lists derived from nuclear magnetic resonance (NMR) spectra are commonly used as input data for a variety of computer assisted and automated analyses. These include automated protein resonance assignment and protein structure calculation software tools. Prior to these analyses, peak lists must be aligned to each other and sets of related peaks must be grouped based on common chemical shift dimensions. Even when programs can perform peak grouping, they require the user to provide uniform match tolerances or use default values. However, peak grouping is further complicated by multiple sources of variance in peak position limiting the effectiveness of grouping methods that utilize uniform match tolerances. In addition, no method currently exists for deriving peak positional variances from single peak lists for grouping peaks into spin systems, i.e. spin system grouping within a single peak list. Therefore, we developed a complementary pair of peak list registration analysis and spin system grouping algorithms designed to overcome these limitations. We have implemented these algorithms into an approach that can identify multiple dimension-specific positional variances that exist in a single peak list and group peaks from a single peak list into spin systems. The resulting software tools generate a variety of useful statistics on both a single peak list and pairwise peak list alignment, especially for quality assessment of peak list datasets. We used a range of low and high quality experimental solution NMR and solid-state NMR peak lists to assess performance of our registration analysis and grouping algorithms. Analyses show that an algorithm using a single iteration and uniform match tolerances approach is only able to recover from 50 to 80% of the spin systems due to the presence of multiple sources of variance. Our algorithm recovers additional spin systems by reevaluating match tolerances in multiple iterations. To facilitate evaluation of the algorithms, we developed a peak list simulator within our nmrstarlib package that generates user-defined assigned peak lists from a given BMRB entry or database of entries. In addition, over 100,000 simulated peak lists with one or two sources of variance were generated to evaluate the performance and robustness of these new registration analysis and peak grouping algorithms.     

Biotransformation of 2,4-dinitroanisole by a fungal <Emphasis Type="Italic">Penicillium</Emphasis> sp.

Insensitive munitions explosives are new formulations that are less prone to unintended detonation compared to traditional explosives. While these formulations have safety benefits, the individual constituents, such as 2,4-dinitroanisole (DNAN), have an unknown ecosystem fate with potentially toxic impacts to flora and fauna exposed to DNAN and/or its metabolites. Fungi may be useful in remediation and have been shown to degrade traditional nitroaromatic explosives, such as 2,4,6-trinitrotoluene and 2,4-dinitrotoluene, that are structurally similar to DNAN. In this study, a fungal Penicillium sp., isolated from willow trees and designated strain KH1, was shown to degrade DNAN in solution within 14 days. Stable-isotope labeled DNAN and an untargeted metabolomics approach were used to discover 13 novel transformation products. Penicillium sp. KH1 produced DNAN metabolites resulting from ortho- and para-nitroreduction, demethylation, acetylation, hydroxylation, malonylation, and sulfation. Incubations with intermediate metabolites such as 2-amino-4-nitroanisole and 4-amino-2-nitroanisole as the primary substrates confirmed putative metabolite isomerism and pathways. No ring-cleavage products were observed, consistent with other reports that mineralization of DNAN is an uncommon metabolic outcome. The production of metabolites with unknown persistence and toxicity suggests further study will be needed to implement remediation with Penicillium sp. KH1. To our knowledge, this is the first report on the biotransformation of DNAN by a fungus.     

Disinfection of bacteriophage MS2 by copper in water

Applied Microbiology and Biotechnology - Households that lack piped water supply are often forced to meet water needs by storing in the home, leaving water vulnerable to contamination by viruses....     

Disease-associated change in an amphibian life-history trait

Oecologia - Emerging pathogens can drive evolutionary shifts in host life-history traits, yet this process remains poorly documented in vertebrate hosts. Amphibian chytridiomycosis, caused by...     

The association of fecal microbiota and fecal,blood serum and urine metabolites in myalgic encephalomyelitis/chronic fatigue syndrome

Introduction

The human gut microbiota has the ability to modulate host metabolism. Metabolic profiling of the microbiota and the host biofluids may determine associations significant of a host–microbe relationship. Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a long-term disorder of fatigue that is poorly understood, but has been linked to gut problems and altered microbiota.

Objectives

Find changes in fecal microbiota and metabolites in ME/CFS and determine their association with blood serum and urine metabolites.

Methods

A workflow was developed that correlates microbial counts with fecal, blood serum and urine metabolites quantitated by high-throughput ¹H NMR spectroscopy. The study consists of thirty-four females with ME/CFS (34.9?±?1.8 SE years old) and twenty-five non-ME/CFS female (33.0?±?1.6 SE years old).

Results

The workflow was validated using the non-ME/CFS cohort where fecal short chain fatty acids (SCFA) were associated with serum and urine metabolites indicative of host metabolism changes enacted by SCFA. In the ME/CFS cohort a decrease in fecal lactate and an increase in fecal butyrate, isovalerate and valerate were observed along with an increase in Clostridium spp. and a decrease in Bacteroides spp. These differences were consistent with an increase in microbial fermentation of fiber and amino acids to produce SCFA in the gut of ME/CFS patients. Decreased fecal amino acids positively correlated with substrates of gluconeogenesis and purine synthesis in the serum of ME/CFS patients.

Conclusion

Increased production of SCFA by microbial fermentation in the gut of ME/CFS patients may be associated with deleterious effects on the host energy metabolism.