Biology subjects

Rubin, T.

Publications and source records attributed to Rubin, T..

5 recordsLinked to original sources

bioRxiv2025

Harnessing artificial intelligence to automate environmental predictions

Predicting heterogeneous and non-linear processes remains a fundamental challenge in Earth sciences. Here, we present an artificial intelligence (AI)-guided framework that iteratively combines predictive modeling with targeted field sampling to rapidly improve environmental predictions. We demonstrate our workflow by predicting oxygen consumption, a key process of stream metabolism, across the contiguous United States (CONUS). Our approach consisted of 18 iterative loops of measurements and models, combining distributed participatory field sampling, lab analysis, automated machine learning (ML) predictions, and error and distinctiveness analyses to autonomously guide the next sampling at optimal site locations. Through our approach, we increased the predictive power of sediment oxygen consumption across CONUS by over fifteenfold between the first and last iteration. Relative to our last sampling iteration, our first sampling missed sites with high rates and underestimated median oxygen consumption rates by 68%. In addition to identifying areas of high oxygen consumption rates, iterations enabled refinement of laboratory and data handling methods, and engagement with a broad community of field researchers. We conclude that AI-guided iterative loops between targeted sampling and predictive modeling are a powerful and efficient approach for improving predictions of heterogeneous environmental processes.

ecology↗

bioRxiv2024

Transcriptomic analysis of meiotic genes during the mitosis-to-meiosis transition in Drosophila females

Germline cells produce gametes, which are specialized cells essential for sexual reproduction. Germline cells first amplify through several rounds of mitosis before switching to the meiotic program, which requires specific sets of proteins for DNA recombination, chromosome pairing and segregation. Surprisingly, we previously found that some proteins of the synaptonemal complex, a prophase I meiotic structure, are already expressed and required in the mitotic region of Drosophila females. Here, to assess if additional meiotic genes were expressed earlier than expected, we isolated mitotic and meiotic cell populations to compare their RNA content. Our transcriptomic analysis reveals that all known meiosis I genes are already expressed in the mitotic region, however, only some of them are translated. As a case study, we focused on mei-W68, the Drosophila homologue of Spo11, to assess its expression at both the mRNA and protein levels, and used different mutant alleles to assay for a pre-meiotic function. We could not detect any functional role for Mei-W68 during homologous chromosome pairing in dividing germ cells. Our study paves the way for further functional analysis of meiotic genes expressed in the mitotic region. Article SummaryGermline cells, crucial for sexual reproduction, were thought to switch to meiosis only after several rounds of mitosis. Surprisingly, a few meiotic proteins were found active in the mitotic phase of female flies. Here, we discovered that all known meiosis genes were expressed during mitosis, but only some produced proteins. This study suggests that genes related to reproduction are active earlier than expected, prompting further exploration into their functions during early cell division.

developmental biology↗

bioRxiv2021

Pre-meiotic pairing of homologous chromosomes during Drosophila male meiosis

In the early stages of meiosis, maternal and paternal chromosomes pair with their homologous partner and recombine to ensure exchange of genetic information and proper segregation. These events can vary drastically between species and between males and females of the same species. In Drosophila, in contrast to females, males do not form synaptonemal complexes (SCs), do not recombine and have no crossing-over; yet, males are able to segregate their chromosomes properly. Here, we investigated the early steps of homologues pairing in Drosophila males. We found that homologues are not paired in germline stem cells (GSCs) and become paired in the mitotic region before meiotic entry, similarly to females. Surprisingly, male germline cells express SC proteins, which localize to centromeres and promote pairing. We further found that the SUN/KASH (LINC) complex and microtubules are required for homologues pairing as in females. Chromosome movements are however much slower than in females and we demonstrate that this slow dynamic is compensated in males by having longer cell cycles. In agreement, slowing down cell cycles was sufficient to rescue pairing-defective mutants in female meiosis. Our results demonstrate that although meiosis differs significantly between males and females, sex-specific cell cycle kinetics are integrated with similar molecular mechanisms to achieve proper homologues pairing.

developmental biology↗

bioRxiv2019

Centromere clustering stabilizes meiotic homolog pairing

During meiosis, each chromosome must selectively pair and synapse with its own unique homolog to enable crossover formation and subsequent segregation. How homolog pairing is maintained in early meiosis to ensure synapsis occurs exclusively between homologs is unknown. We aimed to further understand this process by utilizing a unique Drosophila meiotic mutant, Mcm5A7. We found that Mcm5A7 mutants are proficient in homolog pairing at meiotic onset yet fail to maintain pairing as meiotic synapsis ensues, causing seemingly-normal synapsis between non-homologous loci. This pairing defect corresponds with a reduction of SMC1-dependent centromere clustering at meiotic onset. Overexpressing SMC1 in this mutant significantly restores centromere clustering, homolog pairing, and crossover formation. These data indicate that the initial meiotic pairing of homologs is not sufficient to yield synapsis between exclusively between homologs and provide a model in which meiotic homolog pairing must be stabilized by SMC1-dependent centromere clustering to ensure proper synapsis.

cell biology↗

bioRxiv2019

Differential Metabolic Sensitivity of mTORC1- and mTORC2-Dependent Overgrowth

The glycolytic/lipogenic axis promotes the synthesis of energetic molecules and building blocks necessary to support cell growth, although the absolute requirement of this metabolic axis must be deeply investigated. Here, we used Drosophila genetics and focus on the mTOR signaling network that controls cell growth and homeostasis. mTOR is present in two distinct complexes, mTORC1 and mTORC2. The former directly responds to amino acids and energetic levels, whereas the latter is required to sustain the signaling response downstream of insulin-like-peptide (Ilp) stimulation. Either signaling branch can be independently modulated in most Drosophila tissues. We confirm this independency in the fat tissue. We show that ubiquitous over-activation of mTORC1 or Ilp signaling affects carbohydrate and lipid metabolism, supporting the use of Drosophila as a powerful model to study the link between growth and metabolism. We show that cell-autonomous restriction of glycolysis or lipogenesis in fat cells impedes overgrowth dependent on Ilp-but not mTORC1-signaling. Additionally, ubiquitous deficiency of lipogenesis (FASN mutants) results in a drop in mTORC1 but not Ilp signaling, whereas, at the cell-autonomous level, lipogenesis deficiency affects none of these signals in fat cells. These findings thus, reveal differential metabolic sensitivity of mTORC1- and Ilp-dependent overgrowth. Furthermore, they suggest that local metabolic defects may elicit compensatory pathways between neighboring cells, whereas enzyme knockdown in the whole organism results in animal death. Importantly, our study weakens the use of single inhibitors to fight mTOR-related diseases and strengthens the use of drug combination and selective tissue-targeting.

cell biology↗