Biology subjects

Theus, M.

Publications and source records attributed to Theus, M..

3 recordsLinked to original sources

bioRxiv2025

Higher methanotroph abundance and bottom-water methane in ponds with floating photovoltaic arrays

Floating photovoltaic (FPV) arrays alter the methane (CH4) cycling dynamics of waterbodies on which they are deployed. Here, we investigated dissolved CH4 dynamics and associated CH4 cycling microbial communities (methanogens and methanotrophs) in the second year of FPV deployment (70% aerial coverage) in experimental ponds. We found that bottom-water CH4 concentrations were twice as high in ponds with FPV compared to those without, while surface water CH4 concentrations were orders of magnitude lower than bottom-waters, but did not differ between treatments. There was no change in the relative abundances of putative sediment methanogens or methanotrophs, but FPV restructured methanogen communities. FPV promoted late-summer methanotroph blooms in the water column, with abundances surpassing 1,000,000 cells mL-1. We conclude that prolonged periods of CH4 production in low oxygen FPV ponds favored blooms of methanotrophs, that may mitigate diffusive CH4 emissions to the atmosphere by consuming dissolved CH4.

ecology↗

bioRxiv2025

Tie2-Dependent Mechanisms Promote Leptomeningeal Collateral Remodeling and Reperfusion Following Stroke

Leptomeningeal collaterals are distal pial arterial anastomotic vessels that provide an alternative route for redistributing cerebral blood flow following arterial obstruction, thereby limiting tissue damage. However, the regulatory mechanisms and strategies to enhance this adaptive response remain under investigation. This study explored the pharmacological effects of Tie2 receptor activation, using the peptide agonist Vasculotide, following permanent middle cerebral artery occlusion (pMCAO). Vasculotide improved collateral growth and remodeling, which correlated with reduced infarct volume, enhanced blood flow, and functional recovery within 24hrs post-pMCAO. In contrast, collateral growth was attenuated in Tie2 and EphA4/Tie2 double knockdown mice, while the loss of EphA4 increased Tie2 and Ang-1 expression and mimicked the positive effects of Vasculotide following stroke. Furthermore, bulk RNA sequencing of meningeal tissue identified key transcriptomic changes, including alterations in AJ-associated transcripts, such as Krt5, Krt14, and Col17a1, in the ipsilateral meninges of both endothelial cell-specific EphA4 knockout and Vasculotide-treated mice. Krt5 expression was found upregulated on meningeal arterial vascular network in injured KO mice, highlighting a potential new mediator of meningeal vascular remodeling. These findings illustrate that EphA4 and Tie2 play opposing roles in collateral remodeling, including the regulation of Krt5. Modulating their activity could potentially enhance the collateral response to stroke.

neuroscience↗

bioRxiv2024

Machine Learning Identifies Genes Linked to Neurological Disorders Induced by Equine Encephalitis viruses (EEV), Traumatic Brain Injuries (TBI), and Organophosphorus nerve agents (OPNA)

Venezuelan, eastern, and western equine encephalitis viruses (collectively referred to as equine encephalitis viruses---EEV) cause serious neurological diseases and are a significant threat to the civilian population and the warfighter. Likewise, organophosphorus nerve agents (OPNA) are highly toxic chemicals that pose serious health threats of neurological deficits to both military and civilian personnel around the world. Consequently, only a select few approved research groups are permitted to study these dangerous chemical and biological warfare agents. This has created a significant gap in our scientific understanding of the mechanisms underlying neurological diseases. Valuable insights may be gleaned by drawing parallels to other extensively researched neuropathologies, such as traumatic brain injuries (TBI). By examining combined gene expression profiles, common and unique molecular characteristics may be discovered, providing new insights into medical countermeasures (MCMs) for TBI, EEV infection and OPNA neuropathologies and sequelae. In this study, we collected transcriptomic datasets for neurological disorders caused by TBI, EEV, and OPNA injury, and implemented a framework to normalize and integrate gene expression datasets derived from various platforms. Effective machine learning approaches were developed to identify critical genes that are associated, either shared among the three neuropathologies or to either TBI, EEV, and OPNA. With the aid of deep neural networks, we were able to extract important association signals for accurate prediction of different neurological disorders by using integrated gene expression datasets of VEEV, OPNA, and TBI samples. Gene ontology and pathway analyses further identified neuropathologic features with specific gene product attributes and functions, shedding light on the fundamental biology of these neurological disorders. Collectively, we highlight a workflow to analyze published transcriptomic data using machine learning, which can be used for both identification of gene biomarkers that are unique to specific neurological conditions, as well as genes shared across multiple neuropathologies. These shared genes could serve as potential neuroprotective drug targets for conditions like EEV, TBI, and OPNA.

neuroscience↗