Biology subjects

Sue, A.

Publications and source records attributed to Sue, A..

3 recordsLinked to original sources

bioRxiv2025

An All-In-One Software Solution for Automated Processing of LA-ICP-TOF-MS datasets

LA-ICP-TOF-MS provides rapid, high resolution elemental analysis of biological and non-biological samples. However, accurate real-time data analysis frequently requires the user to account for several instrumental and experimental variables that can change during data acquisition. AutoSpect is a novel software tool designed to automate the processing and fitting of LA-ICP-TOF-MS data, addressing key challenges such as time-dependent spectral drift, instrument sensitivity drift calibration inaccuracies, and peak deconvolution, enabling researchers to rapidly and accurately process complex datasets. The tool is optimized to be robustly applicable across scientific fields (e.g., geochemistry, biology, and materials science), providing a streamlined solution for end users seeking to maximize the potential of LA-ICP-TOF-MS for high-resolution elemental mapping and isotopic analysis. Significance to JAASAnalysis of fast transient signals using laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS) has become mainstream for elemental mapping. Advancements in LA-ICP-TOF-MS technology continue to accelerate the collective understanding of the role inorganic chemistry plays in dynamic processes. To ensure accurate quantitative results, the vast amount of complex spectral data generated requires elegant solutions to perform a variety of functions including data partitioning, peak fitting, drift correction, mass-to-charge calibration, peak profiling, and spectral fitting. AutoSpect is an all-in-one software solution that provides high level automation with a user-friendly graphical interface to perform complex data analyses for ICP-TOF-MS datasets.

scientific communication and education↗

bioRxiv2025

Autoimmune regulator deficiency causes sterile epididymitis and impacts male fertility through disruption of inorganic physiology

Autoimmune regulator (AIRE), a transcription factor expressed by medullary thymic epithelial cells, is required for shaping the self-antigen tolerant T cell receptor repertoire. Humans with mutations in AIRE suffer from Autoimmune Polyglandular Syndrome Type 1 (APS-1). Among many symptoms, men with APS-1 commonly experience testicular insufficiency and infertility, but the mechanisms causing infertility are unknown. Using an Aire-deficient mouse model, we demonstrate that male subfertility is caused by sterile epididymitis characterized by immune cell infiltration and extensive fibrosis. In addition, we reveal that the presence of autoreactive immune cells and inflammation in epididymides of Aire-deficient mice are required for iron (Fe) deposition in the interstitium, which is brought on by macrophages. We further demonstrate that male subfertility is associated with a decrease in metals zinc (Zn), copper (Cu), and selenium (Se) which serve as cofactors in several antioxidant enzymes. We also show increase in DNA damage of epididymal sperm of Aire-/- animals as a key contributing factor to subfertility. The absence of Aire results in autoimmune attack of the epididymis leading to fibrosis, Fe deposition, and Cu, Zn and Se imbalance, ultimately resulting in sperm DNA damage and subfertility. These results highlight the requirement of Aire to promote immune tolerance throughout the epididymis, disruption of which causes an imbalance of inorganic elements with resulting consequence on male fertility. Key pointsBreakdown of epididymal self-tolerance promotes disruption of inorganic elements. Autoimmunity causes interstitial fibrosis resulting in sperm DNA damage and subfertility. Elevated interstitial iron and macrophages contribute to fibrosis.

pathology↗

bioRxiv2022

Modeling multiphage-bacteria kinetics to predict phage therapy potency and longevity

Pseudomonas aeruginosa is a frequent cause of life-threatening opportunistic infections in the critically ill and immunocompromised. Its treatment is challenging due to the increasing prevalence of resistance to most conventional antibiotics. Although numerous alternative therapies are currently under investigation, bacteriophage (phage) cocktail therapy appears poised for long-term success. Here, we investigate potency and longevity of individual Pseudomonas phages in cocktail to determine viral co-factors that promote optimal treatment efficacy. We combined in vitro and in silico models to predict sixty-eight treatment permutations with three phages that adsorb symmetrically and asymmetrically when administered singly, double simultaneously, or double sequentially. We showed that simultaneously administering two asymmetrically binding phages with high cell lysis efficiencies improved cocktail potency. Use of a higher-potency cocktail, along with a reduction in the net probability of independent gene mutations was associated with prolonged bacterial suppression. Nevertheless, in vitro we almost always observed evolution of multiphage resistance. Simulations also predict that when combining phages with polar potencies, susceptible host cells are monopolized by the more efficiently replicating phage. Thus, further perpetuating the growth demise of the weaker phage in cocktail. Our mathematical model was used to explore and predict changes in phage and bacterial populations that were difficult to measure experimentally. This framework has many inferential and exploratory uses for clinical investigation such as identifying the most sensitive parameters for phage selection and exploring different treatment regimens. Collectively, our findings attempt to dissect the mechanisms of phage cocktails combating P. aeruginosa infections and highlight the viral co-factors necessary for treatment efficacy.

microbiology↗