Scholarworks

ScholarWorks is an open access repository for the capture of the intellectual work of Montana State University (MSU) in support of its teaching, research and service missions. MSU ScholarWorks is a central point of discovery for accessing, collecting, sharing, preserving, and distributing knowledge to the Montana State University community and the world.

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Multimerized Epitope Tags for High Sensitivity Protein Detection
(Oxford University Press, 2025-04) Steven, Stowers R.
A detailed understanding of the function of a gene requires knowledge of the cellular and subcellular distribution of its encoded protein(s). For proteins expressed at low levels, antibodies that recognize single epitopes may not be sufficient for visualizing expression. To enhance the sensitivity of protein detection, tandem repeat multimers of the commonly used epitope tags V5, HA, MYC, FLAG, ALFA, and OLLAS were developed that encode up to 80X copies of each tag, an 8-fold increase over currently available options for epitope multimer tagging. As proof-of-principle, conditional alleles of vGlut containing the 40XV5 and 40XMYC epitope tag multimers were validated in vivo in Drosophila. Both epitope-tagged proteins were determined to exhibit synaptic localization in the adult brain and larval neuromuscular junction similar to that of endogenous vGlut. They were also conditionally expressed in subsets of adult brain neurons and observed to exhibit robust, easily detectable expression in presynaptic terminals even in single neurons. These highly multimerized epitope tags will facilitate any type of experiment using antibody detection of proteins that would benefit from enhanced sensitivity.
Ionized Gas Outflows in the Galaxy and Mass Assembly (GAMA) Survey: Signatures of AGN Feedback in Low-mass Galaxies
(American Astronomical Society, 2025-01) Salehirad, Sheyda; Reines, Amy E.; Molina, Mallory
We present a sample of 398 galaxies with ionized gas outflow signatures in their spectra from the Galaxy and Mass Assembly Survey Data Release 4, including 45 low-mass galaxies with stellar masses M* < 1010M⊙. We assemble our sample by systematically searching for the presence of a second velocity component in the [O iii]λλ4959, 5007 doublet emission line in 39,612 galaxies with redshifts z < 0.3. The host galaxies are classified using the Baldwin–Phillips–Terlevich diagram, with ~89% identified as active galactic nuclei (AGNs) and composites and 11% as star-forming (SF) galaxies. The outflows are typically faster in AGNs with a median velocity of 936 km s−1 compared to 655 km s−1 in the SF objects. Of particular interest are the 45 galaxies in the low-mass range, of which a third are classified as AGNs/composites. The outflows from the low-mass AGNs are also faster and more blueshifted compared to those in the low-mass SF galaxies. This indicates that black hole outflows can affect host galaxies in the low-mass range and that AGN feedback in galaxies with M* < 1010M⊙ should be considered in galaxy evolution models.
Assessment of Climate-resilient Cotton Genotypes Exhibiting High-temperature Tolerance
(Springer Science and Business Media LLC, 2025-04) Ali, Sajid; Shafqat Chattha, Waqas; Ullah, Aziz; Ihsan, Muhammad Zahid; Shafqat, Waqar; Ghazy, Abdelhalim I.; Afzal, Muhammad; Ayub, B.
Cotton is an important natural fiber worldwide. Abiotic factors such as high temperature stress reduce seed cotton production and fibre quality. The current research aims to screen cotton germplasm for high temperature tolerance. For this, 60 cotton genotypes were tested for two years with varying sowing dates. Split plot design was used to plant these genotypes after RCBD. The main plot sowing dates and sub-plot cotton genotypes were considered for both years. We recorded boll weight (BW), chlorophyll content (CC), cell membrane thermal stability (CMT), canopy temperature (CT), node number to first fruiting branch (NNFFB), and seed cotton yield (SCY). Heat-stress-tolerant cotton germplasm can be created by analyzing genetic variation, genotype-environment interaction, and characteristics associated with SCY. Studying the Genotype × Environment Interaction (GEI) of cotton genotypes for specified agro-physiological parameters using GGE biplot analysis. The genotypes FH Lalazar, MNH-1016, PB-76, MNH-992, and FH-458 are either stable or show positive interaction with high temperature stress conditions for most traits under study, suggesting they can be used in future breeding programs to develop heat stress-tolerant varieties. The correlation coefficients also showed that all traits except node number to first fruiting branch and canopy temperature were positively and significantly correlated with seed cotton yield under heat stress, suggesting that using one or more of these traits as selection criteria could increase cotton yield under heat stress.
Robust estimation under a semiparametric propensity model for nonignorable missing data
(Institute of Mathematical Statistics, 2025-01) Shetty, Samidha; Ma, Yanyuan; Zhao, Jiwei
We study the problem of estimating a functional or a parameter in the context where outcome is subject to nonignorable missingness. We completely avoid modeling the regression relation between outcome and covariates, while allowing the propensity to be modeled by a semiparametric relation where the dependence on covariates is unknown and unspecified. This unknown function in the semiparametric propensity model is not directly estimable from the observed data and is the fundamental challenge in the estimation of the parameter of interest. By carefully analyzing the semiparametric structure of the model, we discover that the estimation of the parameter in the propensity model as well as the functional estimation can be carried out without estimating this unknown function. This phenomenon is especially interesting and extremely helpful in our context, because it overcomes the very obstacle that this unknown function cannot be directly estimated from the observed data. The property of the proposed estimator is established rigorously through theoretical derivations, and supported by simulations and a data application.
Heme and iron limitation in a GI-tract foundation species leads to a reshuffling of the metalloproteome and a shift toward manganese usage
(Frontiers Media SA, 2025-04) Rodrigues da Silva, Ronivaldo; Larson, James; Bothner, Brian; DuBois, Jennifer
The metal-binding complement of the cellular proteome (the metalloproteome) depends on metal availability in the cellular environment and drives cellular metabolism. Bacteroides thetaiotaomicron (Bacteroides theta) is a foundational species in the anaerobic gut microbiome and a heme auxotroph, though little is known about why it requires heme. We hypothesized that B. theta would overproduce heme-binding proteins in response to limitations in non-heme iron, and reciprocally, activate non-heme iron pathways when heme was growth limiting. Here we showed that heme and/or non-heme iron scarcity triggers a more holistic reorganization of its metallome and metalloproteome. Under non-heme iron limitation induced by an Fe(II)-specific chelator, manganese supplementation restored growth, suggesting manganese can partly compensate for non-heme iron. Metalloproteomic analyses using tandem HPLC-ICP-MS revealed significant changes in the distribution of zinc, manganese, and iron in response to varying iron or heme availability. These findings highlight the interplay between heme/non-heme iron and the metallome in bacterial growth regulation, and they underscore a role for manganese under iron scarcity.