Biology subjects

Shimada, K.

Publications and source records attributed to Shimada, K..

26 records · Page 2Linked to original sources

bioRxiv2022

1700029I15Rik orchestrates the biosynthesis of acrosomal membrane proteins required for sperm-egg fusion

Sperm acrosomal membrane proteins, such as IZUMO1 and SPACA6, play an essential role in mammalian sperm-egg fusion. How their biosynthesis is regulated during spermiogenesis has largely remained unknown. Here, we show that the 1700029I15Rik knockout male mice are severely subfertile and their spermatozoa do not fuse with eggs. 1700029I15Rik encodes a type-II transmembrane protein that is expressed in early spermatids but not in mature spermatozoa. 1700029I15Rik is associated with proteins involved in N-glycosylation, disulfide isomerisation, and ER- Golgi trafficking, suggesting its involvement in nascent protein processing. 1700029I15Rik knockout testis has a normal level of sperm plasma membrane proteins, but decreased expression of multiple acrosomal membrane proteins. The knockout sperm exhibit elevated ubiquitinated proteins and upregulated ER-associated degradation; strikingly, SPACA6 becomes undetectable. Our results support for a specific, 1700029I15Rik-mediated pathway in spermiogenesis for the assembly of acrosomal membrane proteins. Significance StatementIn sexually reproducing species, life begins with the fusion between a sperm and an egg. Multiple sperm acrosomal membrane proteins have been reported indispensable for sperm-egg fusion in mammals, yet the mechanism underlying their biosynthesis remains unknown. The present study demonstrates the existence of a 1700029I15Rik-mediated pathway specifically coordinating the processing and assembly of acrosomal membrane proteins. It represents an intriguing paradigm where the biosynthesis of proteins destined for various subcellular compartments might be orchestrated in a spatiotemporal manner. Given 1700029I15Rik is highly conserved in human, our findings provide potential insights into the aetiology of idiopathic male infertility and the development of a novel contraceptive approach involving molecular interventions in the maturation of gamete fusion-required acrosomal proteins.

developmental biology↗

bioRxiv2021

LRRC23 is a conserved component of the radial spoke that is necessary for sperm motility and male fertility in mice

Cilia and flagella are ancient structures that achieve controlled motor functions through the coordinated interaction of structures including dynein arms, radial spokes (RSs), microtubules, and the dynein regulatory complex (DRC). RSs facilitate the beating motion of these organelles by mediating signal transduction between dyneins and a central pair (CP) of singlet microtubules. RS complex isolation from Chlamydomonas axonemes enabled the detection of 23 different proteins (RSP1-23), with the roles of RSP13, RSP15, RSP18, RSP19, and RSP21 remained poorly understood. Herein, we show that Lrrc23 is an evolutionarily conserved testis-enriched gene encoding an RSP15 homolog in mice. Through immunoelectron microscopy, we demonstrate that LRRC23 localizes to the RS complex within murine sperm flagella. We further found that LRRC23 was able to interact with RSHP9 and RSPH3A/B. The knockout of Lrrc23 resulted in RS disorganization and impaired motility in murine spermatozoa, whereas the ciliary beating was unaffected by the loss of this protein. Spermatozoa lacking LRRC23 were unable to efficiently pass through the uterotubal junction and exhibited defective zona penetration. Together these data indicate that LRRC23 is a key regulator underpinning the integrity of RS complex within the flagella of mammalian spermatozoa, whereas it is dispensable in cilia. Author summary

cell biology↗

bioRxiv2021

The neural correlates of semantic and grammatical encoding during sentence production in a second language: evidence from an fMRI study using syntactic priming

Japanese English learners have difficulty speaking Double Object (DO; give B A) than Prepositional Object (PO; give A to B) structures which neural underpinning is unknown. In speaking, syntactic and phonological processing follow semantic encoding, conversion of non-verbal mental representation into a structure suitable for expression. To test whether DO difficulty lies in linguistic or prelinguistic process, we conducted functional magnetic resonance imaging. Thirty participants described cartoons using DO or PO, or simply named them. Greater reaction times and error rates indicated DO difficulty. DO compared with PO showed parieto-frontal activation including left inferior frontal gyrus, reflecting linguistic process. Psychological priming in PO produced immediately after DO and vice versa compared to after control, indicated shared process between PO and DO. Cross-structural neural repetition suppression was observed in occipito-parietal regions, overlapping the linguistic system in pre-SMA. Thus DO and PO share prelinguistic process, whereas linguistic process imposes overload in DO.

neuroscience↗

bioRxiv2021

Destabilization of the holo-DNA Polδ by loss of Pol32 confers conditional lethality that can be suppressed by stabilizing Pol31-Pol3 interaction

DNA Polymerase {delta} plays an essential role in genome replication and in the preservation of genome integrity. In S. cerevisiae, Pol{delta} consists of three subunits: Pol3 (the catalytic subunit), Pol31 and Pol32. We have constructed pol31 mutants by alanine substitution at conserved amino acids, and identified three alleles that do not confer any disadvantage on their own, but which suppress the cold-, HU- and MMS-hypersensitivity of yeast strains lacking Pol32. We have shown that Pol31 and Pol32 are both involved in translesion synthesis, error-free bypass synthesis, and in preservation of replication fork stability under conditions of HU arrest. We identified a solvent exposed loop in Pol31 defined by two alanine substitutions at T415 and W417. Whereas pol31-T4l5A compromises polymerase stability at stalled forks, pol31-W417A is able to suppress many, but not all, of the phenotypes arising from pol32{Delta}. ChIP analyses showed that the absence of Pol32 destabilizes Pole and Pol at stalled replication forks, but does not interfere with checkpoint kinase activation. We show that the Pol31-W417A-mediated suppression of replicationstress sensitivity in pol32{Delta} stems from enhanced interaction between Pol3 and Pol31, which stabilizes a functional Pol{delta}.

molecular biology↗

bioRxiv2020

Uncoordinated long-patch base excision repair at juxtaposed DNA lesions generates a lethal accumulation of double-strand breaks

Inhibition of the TOR pathway (TORC2, or Ypk1/2), or the depolymerization of actin filaments results in catastrophic fragmentation of the yeast genome upon exposure to low doses of the radiomimetic drug Zeocin. We find that the accumulation of double-strand breaks (DSB) is not due to altered DSB repair, but by the uncoordinated activity of base excision repair (BER) at Zeocin-modified DNA bases. We inhibit DSB formation by eliminating glycosylases and/or the endonucleases Apn1/2 and Rad1, implicating these conserved BER enzymes, or events downstream of them, in the conversion of base damage into DSBs. Among DNA polymerases, the reduction of Pol {delta}, and to a lesser extent Pol {varepsilon} and Trf4 (a Pol {beta}-like polymerase), reduces DSB formation. Finally, the BER enzymes, Ogg1 and AP endonuclease, are shown to co-precipitate with actin from yeast extracts and as purified proteins, suggesting that actin may interfere directly with the repair of Zeocin-induced damage.

molecular biology↗

bioRxiv2019

A tool for browsing the Cancer Dependency Map reveals functional connections between genes and helps predict the efficacy and selectivity of candidate cancer drugs

Individual cancers rely on distinct essential genes for their survival. The Cancer Dependency Map (DepMap) is an ongoing project to uncover gene dependency in hundreds of cancer cell lines. DepMap is a powerful drug discovery tool, but can be challenging to use without professional bioinformatics assistance. We combined CRISPR and shRNA screening data from DepMap and built a non-programmer-friendly browser (https://labsyspharm.shinyapps.io/depmap) that reports, for each gene, the growth reduction that can be expected on loss of a gene or inhibition of its action (efficacy) and the selectivity of this effect across cell lines. Cluster analysis revealed proteins that work together in pathways or complexes. This tool can be used to 1) predict the efficacy and selectivity of candidate drugs; 2) identify targets for highly selective drugs; 3) identify maximally sensitive cell lines for testing a drug; 4) target hop, i.e., navigate from an undruggable protein with the desired selectively profile, such as an activated oncogene, to more druggable targets with a similar profile; and 5) identify novel pathways needed for cancer cell growth and survival.

cancer biology↗

bioRxiv2018

Genome-wide association meta-analysis identifies novel GP2 gene risk variants for pancreatic cancer in the Japanese population

The etiology of pancreatic cancer remains largely unknown. Here, we report the results of a meta-analysis of three genome-wide association studies (GWASs) comprising 2,039 pancreatic cancer cases and 32,592 controls, the largest sample size in the Japanese population. We identified 3 (13q12.2, 13q22.1, and 16p12.3) genome-wide significant loci (P<5.0x10-8) and 4 suggestive loci (P<1.0x10-6) for pancreatic cancer. Of these risk loci, 16p12.3 is novel; the lead SNP maps to rs78193826 (odds ratio (OR)=1.46, 95% CI=1.29-1.66, P=4.28x10-9), an Asian-specific, nonsynonymous glycoprotein 2 (GP2) gene variant predicted to be highly deleterious. Additionally, the gene-based GWAS identified a novel gene, KRT8, which is linked to exocrine pancreatic and liver diseases. The identified GP2 gene variants were pleiotropic for multiple traits, including type 2 diabetes, hemoglobin A1c (HbA1c) levels, and pancreatic cancer. Mendelian randomization analyses corroborated causality between HbA1c and pancreatic cancer. These findings suggest that GP2 gene variants are associated with pancreatic cancer susceptibility in the Japanese population, prompting further functional characterization of this locus.

genetics↗

bioRxiv2018

Machine characterization of rat toxin responses identifies disease states, tolerance mechanisms and organ to whole-body communication

BackgroundLiving organisms are constantly exposed to toxic xenobiotics and have therefore evolved protective responses. In mammals, the liver and kidney play central roles in protecting the organism from xenobiotics, and are at high risk of xenobiotic-induced injury. Liver and kidney damage by drugs and industrial toxins have been extensively studied from both classical histopathologic and biochemical perspectives.\n\nMethods and FindingsWe introduce a machine learning approach for the analysis of toxicological response. Unsupervised characterization of physiological and histological changes in a large toxicogenomic dataset revealed nine discrete toxin-induced disease states. Transcriptome analysis showed that some of the machine-identified disease states correspond to known pathology, and to known effects of certain toxin classes, but others were novel. Analysis of dynamics revealed transitions between disease states at constant toxin exposure, mostly in the direction of decreased pathology, which implies induction of tolerance. Tolerance correlated with induction of known xenobiotic defense genes and novel decreased ferroptosis sensitivity biomarkers. These data reinforce emerging evidence that ferroptosis drives organ pathology, and suggest that its downreagulation may promote tolerance and recovery. Lastly, mechanism of body weight decrease, a known primary marker for toxicity, was investigated. Combined analysis of food consumption, body weight, and molecular biomarkers indicated that organ disease states promote cachexia by whole-body signaling through Gdf15 and Igf1, suggesting strategies for therapeutic intervention that may be broadly relevant to human disease.\n\nConclusionsApplication of machine learning to systematic data collection of physiology, histopathology, transcriptome reveals multiple disease states, tolerance mechanisms and organ to whole-body communication.

systems biology↗