Biology subjects

Kimmel, J.

Publications and source records attributed to Kimmel, J..

5 recordsLinked to original sources

bioRxiv2026

Gonadal PIP-seq reveals genes involved in germ cell development and sexual differentiation in sea lamprey ( Petromyzon marinus )

Vertebrate sex determination is highly diverse, with distinct mechanisms that have evolved repeatedly and independently across phylogeny. The sea lamprey (Petromyzon marinus) is an extant jawless vertebrate that remains sexually labile during its larval stage that lasts around 3-20 years. Their gonad contains bipotential, female, and male germ cells before metamorphosis. To examine the genetic programs in germ cells at different developmental stages, we profiled transcriptomes of dissociated gonadal cells from larvae and recently metamorphosed juvenile (transformers, sex-determined) using fluorescence-activated cell sorting (BD FACS Aria IIu) and PIPseqTM (Fluent BioSciences/Illumina). 66,676 cells were sequenced and classified into 19 cell clusters according to their gene expression profiles. Primordial germ cells differentially expressed genes encoding various heat-shock proteins, hormones, growth factors, and their receptors, and proteins sensitive to iron, nitrogen starvation, sugar and lipid metabolisms, and oxidative stress, providing possible links between environmental factors, cellular functions, and cell fate determinants. Germ cells in larvae had enriched expression of genes involved in DNA replication, transcription, translation, apoptosis, autophagy, cell cycle, cell differentiation, cell adhesion and migration, cell survival, chromatin remodeling, and proliferation. Specifically, female germ cells differentially expressed various transcript isoforms of AEP1, CUZD1, S100A1, and ZP genes, whereas male germ cells differentially expressed BOLL and PIWIL1. Pseudotime trajectory and Gene Ontology (GO) analysis revealed that genes with changing expressions along the female differentiation pathway were involved in binding of sperm to zona pellucida, egg coat formation, prevention of polyspermy and positive regulation of acrosome reaction. On the other hand, genes with changing expressions along the male differentiation pathway were involved in ribosome assembly and translation. Several WNT5 transcripts were differentially expressed in germ cells or somatic cells. Our results suggest that sea lamprey sex determination and sexual differentiation likely involve the coordinated action of numerous genes that interact with various environmental factors and regulate germ cell specification and development.

Developmental Biology↗

bioRxiv2025

Protein landscape of the chromatin states in the malaria parasite Plasmodium falciparum

Epigenetic regulation is essential for development and adaptation across eukaryotes. However, a comprehensive overview of the molecular framework of chromatin-mediated regulation, particularly in non-model organisms, is lacking. Here, we present a systematic proteomic characterization of the chromatin states in P. falciparum, an ancient human pathogen with unique genome composition and epigenetic blueprint. We adapted and systematically employed three proximity-labelling approaches to provide a high-confidence and comprehensive proteome of heterochromatin, euchromatin and (peri)centromeric chromatin comprised of 214 proteins, including both expected and new chromatin components. Characterization of 20 proteins validated our approach and i) uncovered a protein influencing parasite transmission, ii) defined complexes relevant for histone variant exchange and chromatin-RNA interactions and iii) provided evidence for the so far believed to be absent spindle assembly checkpoint and the corresponding Bub1-like kinase. This study hence offers a reference proteome of the chromatin states and a resource to uncover novel chromatin biology.

cell biology↗

bioRxiv2022

Gene-by-gene screen of the unknown proteins encoded on P. falciparum chromosome 3

Taxa-specific proteins are key determinants defining the biology of all organisms and represent prime drug targets in pathogens. However, lacking comparability with proteins in other lineages makes them particularly difficult to study. In malaria parasites this is exacerbated by technical limitations. Here, we analysed the cellular location, essentiality, function and, in selected cases, interactome of all unknown non-secretory proteins encoded on an entire P. falciparum chromosome. The nucleus was the most common localisation, indicating it is a hotspot of parasite-specific biology. More in-depth functional studies with four proteins revealed essential roles in DNA replication and mitosis. The novel mitosis proteins defined a possible orphan complex and a highly diverged complex needed for the spindle-kinetochore connection. Structure-function comparisons indicated that the taxa-specific proteins evolved by different mechanisms. This work demonstrates the feasibility of gene-by-gene screens to elucidate the biology of malaria parasites and reveal critical parasite-specific processes of interest as drug targets.

cell biology↗

bioRxiv2021

Identification of novel inner membrane complex and apical annuli proteins of the malaria parasite Plasmodium falciparum

The inner membrane complex (IMC) is a defining feature of apicomplexan parasites, which confers stability and shape to the cell, functions as a scaffolding compartment during the formation of daughter cells and plays an important role in motility and invasion during different life cycle stages of these single celled organisms. To explore the IMC proteome of the malaria parasite Plasmodium falciparum we applied a proximity-dependent biotin identification (BioID)-based proteomics approach, using the established IMC marker protein Photosensitized INA-Labelled protein 1 (PhIL1) as bait in asexual blood-stage parasites. Subsequent mass spectrometry-based peptide identification revealed enrichment of twelve known IMC proteins and several uncharacterized candidate proteins. We validated nine of these previously uncharacterized proteins by endogenous GFP-tagging. Six of these represent new IMC proteins, while three proteins have a distinct apical localization that most likely represent structures described as apical annuli in Toxoplasma gondii. Additionally, various Kelch13 interacting candidates were identified, suggesting an association of the Kelch13 compartment and the IMC in schizont and merozoite stages. This work extends the number of validated IMC proteins in the malaria parasite and reveals for the first time the existence of apical annuli proteins in P. falciparum. Additionally, it provides evidence for a spatial association between the Kelch13 compartment and the IMC in late blood-stage parasites.

cell biology↗

bioRxiv2017

Deep convolution neural networks allow analysis of cell motility during stem cell differentiation and neoplastic transformation

Cells in culture display diverse motility behaviors that may reflect differences in cell state and function, providing motivation to discriminate between different motility behaviors. Current methods to do so rely upon manual feature engineering. However, the types of features necessary to distinguish between motility behaviors can vary greatly depending on the biological context, and it is not always clear which features may be most predictive in each setting for distinguishing particular cell types or disease states. Convolutional neural networks (CNNs) are machine learning models allowing for relevant features to be learned directly from spatial data. Similarly, recurrent neural networks (RNNs) are a class of models capable of learning long term temporal dependencies. Given that cell motility is inherently spacio-temporal data, we present an approach utilizing both convolutional and long- short-term memory (LSTM) recurrent neural network units to analyze cell motility data. These RNN models provide accurate classification of simulated motility and experimentally measured motility from multiple cell types, comparable to results achieved with hand-engineered features. The variety of cell motility differences we can detect suggests that the algorithm is generally applicable to additional cell types not analyzed here. RNN autoencoders based on the same architecture are capable of learning motility features in an unsupervised manner and capturing variation between myogenic cells in the latent space. Adapting these RNN models to motility prediction, RNNs are capable of predicting muscle stem cell motility from past tracking data with performance superior to standard motion prediction models. This advance in cell motility prediction may be of practical utility in cell tracking applications.

bioinformatics↗