Biology subjects

Emmons, S.

Publications and source records attributed to Emmons, S..

5 recordsLinked to original sources

bioRxiv2026

Comparing morphological and molecular methods for stream macroinvertebrate biodiversity assessment across seven watersheds in the southern United States

Freshwater biodiversity is declining at alarming rates globally, yet our capacity to monitor it depends heavily on the methods used for biodiversity assessment. Stream benthic macroinvertebrates are widely used as bioindicators, but traditional morphological identification is labor-intensive and limited by taxonomic expertise, while DNA metabarcoding offers a promising but incompletely evaluated alternative. Here, we compared biodiversity patterns detected by four macroinvertebrate sampling and identification methods (morphological identification of benthic samples, morphological identification of combined benthic and stream-edge samples, eDNA metabarcoding of bulk benthic samples, and eDNA metabarcoding of streamwater) across 62 sites in seven watersheds spanning the southern continental United States. We compared methods across three facets of biodiversity (gamma diversity, alpha diversity, and taxonomic composition) and three taxonomic levels (family, genus, and species). We found that which method detected more taxa shifted with taxonomic resolution: morphological methods detected more families and genera, while metabarcoding methods detected more species. Bulk benthic metabarcoding detected more families and genera than water eDNA metabarcoding, consistent with the "watered-down biodiversity" effect of DNA dilution in water samples, but the two metabarcoding methods did not differ significantly in species richness. All four methods detected largely distinct suites of taxa, with metabarcoding methods yielding more unique taxa than morphological methods. Notably, taxa uniquely detected by water eDNA were dominated by soft-bodied organisms (oligochaetes, leeches, earthworms) and water-column-associated taxa, while benthic eDNA uniquely detected hard-bodied EPT insects. We attribute this pattern to fundamental differences in eDNA shedding, transport, and deposition dynamics across organism types. These results demonstrate that no single method captures a complete picture of stream macroinvertebrate biodiversity, and that method choice should be guided by the taxonomic resolution and community components most relevant to the goals of the bioassessment program.

ecology↗

bioRxiv2023

Prediction of Interactions between Cell Surface Proteins by Machine Learning

Cells detect changes of external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions between cell surface proteins are highly dynamic and thus challenging to detect using traditional experimental techniques. Here we tackle this challenge by a computational framework. The primary focus of the framework is to develop new tools to identify interactions between domains in immunoglobulin (Ig) fold, which is the most abundant domain family in cell surface proteins. These interactions could be formed between ligands and receptors from different cells, or between proteins on the same cell surface. In practice, we collected all structural data of Ig domain interactions and transformed them into an interface fragment pair library. A high dimensional profile can be then constructed from the library for a given pair of query protein sequences. Multiple machine learning models were used to read this profile, so that the probability of interaction between the query proteins can be predicted. We tested our models to an experimentally derived dataset which contains 564 cell surface proteins in human. The cross-validation results show that we can achieve higher than 70% accuracy in identifying the PPIs within this dataset. We then applied this method to a group of 46 cell surface proteins in C elegans. We screened every possible interaction between these proteins. Many interactions recognized by our machine learning classifiers have been experimentally confirmed in the literatures. In conclusion, our computational platform serves a useful tool to help identifying potential new interactions between cell surface proteins in addition to current state-of-the-art experimental techniques. The tool is freely accessible for use by the scientific community. Moreover, the general framework of the machine learning classification can also be extended to study interactions of proteins in other domain superfamilies.

bioinformatics↗

bioRxiv2018

A direct glia-to-neuron natural transdifferentiation ensures nimble sensory-motor coordination of male mating behaviour

The coordinated execution of innate, stereotyped sexual behaviours, such as courtship and mating, requires sexually dimorphic sensory-motor circuits that are genetically specified during development (reviewed in [1-3]). Studies in the nematode Caenorhabditis elegans, in which the development and function of neural circuits can be interrogated with single cell resolution, have revealed two general developmental mechanisms underlying sexual dimorphism in the nervous system. The first involves the acquisition of sexually dimorphic features in sex-shared neurons during sexual maturation, which include changes in terminal gene expression, such as odorant receptors, neurotransmitters and synaptic regulators [4-10]. The second mechanism involves the generation of sex-specific neurons [11-13]. This requires sex-specific cell death [14]or neurogenesis events resulting from extensive sex differences in the cell division patterns and neurodevelopmental programmes of post-embryonic cell lineages (reviewed in [3]). Here we identify a third, novel way to generate sexual dimorphism in the nervous system. We find that during sexual maturation (L4 stage), a class of sex-shared glial cells acquires sexually dimorphic function by undergoing a direct glia-to-neuron transdifferentiation that results in the production of male-specific neurons. This plasticity is regulated cell-intrinsically by the sex-determination pathway. These previously unnoticed neurons, which we term PHDs, are putative proprioceptors that regulate male locomotion during specific steps of mating. One of these steps is a novel readjustment movement performed when intromission becomes difficult to achieve. Our results reveal sex-specific direct transdifferentiation as a novel mechanism for generating sex-specific neurons and also show the importance of proprioceptive feedback during the complex steps of mating for successful reproduction.

neuroscience↗

bioRxiv2018

Heparan sulfate molecules mediate synapse formation and function of male mating neural circuits in C. elegans

The nervous system regulates complex behaviors through a network of neurons interconnected by synapses. How specific synaptic connections are genetically determined is still unclear. Male mating is the most complex behavior in C. elegans. It is composed of sequential steps that are governed by more than 3,000 chemical connections. Here we show that heparan sulfates (HS) play a role in the formation and function of the male neural network. Cell-autonomous and non-autonomous 3-O sulfation by the HS modification enzyme HST-3.1/HS 3-O-sulfotransferase, localized to the HSPG glypicans LON-2/glypican and GPN-1/glypican, was specifically required for response to hermaphrodite contact during mating. Loss of 3-O sulfation resulted in the presynaptic accumulation of RAB-3, a molecule that localizes to synaptic vesicles, disrupting the formation of synapses in a component of the mating circuits. We also show that neural cell adhesion protein neurexin promotes and neural cell adhesion protein neuroligin inhibits formation of the same set of synapses in a parallel pathway. Thus, neural cell adhesion proteins and extracellular matrix components act together in the formation of synaptic connections.\n\nAuthor SummaryThe formation of the nervous system requires the function of several genetically-encoded proteins to form complex networks. Enzymatically-generated modifications of these proteins play a crucial role during this process. These authors analyzed the role of heparan sulfates in the process of synaptogenesis in the male tail of C. elegans. A modification of heparan sulfate is required for the formation of specific synapses between neurons by acting cell-autonomously and non-autonomously. Could it be that heparan sulfates and their diverse modifications are a component of the specification factor that neurons use to make such large numbers of connections unique?

neuroscience↗

bioRxiv2017

Multiple conserved cell adhesion protein interactions mediate neural wiring of a sensory circuit in C. elegans

Nervous system function relies on precise synaptic connections. A number of widely-conserved cell adhesion proteins are implicated in cell recognition between synaptic partners, but how these proteins act as a group to specify a complex neural network is poorly understood. Taking advantage of known connectivity in C. elegans, we identified and studied cell adhesion genes expressed in three interacting neurons in the mating circuits of the adult male. Two interacting pairs of cell surface proteins independently promote fasciculation between sensory neuron HOA and its postsynaptic target interneuron AVG: BAM-2/neurexin-related in HOA binds to CASY-1/calsyntenin in AVG; SAX-7/L1CAM in sensory neuron PHC binds to RIG-6/contactin in AVG. A third, basal pathway results in considerable HOA-AVG fasciculation and synapse formation in the absence of the other two. The features of this multiplexed mechanism help to explain how complex connectivity is encoded and robustly established during nervous system development.

neuroscience↗