Plasma cell maintenance and antibody secretion are under the control of Sec22b-mediated regulation of organelle dynamics

Despite the essential role of plasma cells in health and disease, the cellular mechanisms controlling their survival and secretory capacity are still poorly understood. Here, we identified the SNARE Sec22b as a unique and critical regulator of plasma cell maintenance and function. In absence of Sec22b, plasma cells were barely detectable and serum antibody titres were dramatically reduced. Accordingly, Sec22b deficient mice fail to mount a protective immune response. At the mechanistic level, we demonstrated that Sec22b is indispensable for efficient antibody secretion but also for plasma cell fitness through the regulation of the morphology of the endoplasmic reticulum and mitochondria. Altogether, our results unveil a critical role for Sec22b-mediated regulation of plasma cell biology through the control of organelle dynamics.

Beyond Protein Synthesis; The Multifaceted Roles of Tuberin in Cell Cycle Regulation

The ability of cells to sense diverse environmental signals, including nutrient availability and conditions of stress, is critical for both prokaryotes and eukaryotes to mount an appropriate physiological response. While there is a great deal known about the different biochemical pathways that can detect and relay information from the environment, how these signals are integrated to control progression through the cell cycle is still an expanding area of research. Over the past three decades the proteins Tuberin, Hamartin and TBC1D7 have emerged as a large protein complex called the Tuberous Sclerosis Complex. This complex can integrate a wide variety of environmental signals to control a host of cell biology events including protein synthesis, cell cycle, protein transport, cell adhesion, autophagy, and cell growth. Worldwide efforts have revealed many molecular pathways which alter Tuberin post-translationally to convey messages to these important pathways, with most of the focus being on the regulation over protein synthesis. Herein we review the literature supporting that the Tuberous Sclerosis Complex plays a critical role in integrating environmental signals with the core cell cycle machinery.

Multiple UBX proteins reduce the ubiquitin threshold of the mammalian p97-UFD1-NPL4 unfoldase

The unfolding of ubiquitylated proteins by the p97 / Cdc48 ATPase and its ubiquitin receptors Ufd1-Npl4 is essential in many areas of eukaryotic cell biology. Previous studies showed that yeast Cdc48-Ufd1-Npl4 is governed by a quality control mechanism, whereby substrates must be conjugated to at least five ubiquitins. Here we show that substrate processing by mammalian p97-UFD1-NPL4 involves a complex interplay between ubiquitin chain length and additional p97 cofactors. Using disassembly of the ubiquitylated CMG helicase as a model in vitro system, we find that reconstituted p97-UFD1-NPL4 only unfolds substrates with very long ubiquitin chains. However, this high ubiquitin threshold is greatly reduced, to a level resembling yeast Cdc48-Ufd1-Npl4, by the UBXN7, FAF1 or FAF2 partners of mammalian p97-UFD1-NPL4. Stimulation by UBXN7/FAF1/FAF2 requires the UBX domain that connects each factor to p97, together with the ubiquitin-binding UBA domain of UBXN7 and a previously uncharacterised coiled-coil domain in FAF1/FAF2. Furthermore, we show that deletion of the UBXN7 and FAF1 genes impairs CMG disassembly during S-phase and mitosis and sensitises cells to reduced ubiquitin ligase activity. These findings indicate that multiple UBX proteins are important for the efficient unfolding of ubiquitylated proteins by p97-UFD1-NPL4 in mammalian cells.

The interactome of Cryptococcus neoformans Rmt5 reveals multiple regulatory points in fungal cell biology and pathogenesis

Protein arginine methylation is a key post-translational modification in eukaryotes that modulates core cellular processes, including translation, morphology, transcription, and RNA fate. However, this has not been explored in Cryptococcus neoformans, a human-pathogenic basidiomycetous encapsulated fungus. We characterized the five protein arginine methyltransferases in C. neoformans and highlight Rmt5 as critical regulator of cryptococcal morphology and virulence. An rmt5∆ mutant was defective in thermotolerance, had a remodeled cell wall, and exhibited enhanced growth in an elevated carbon dioxide atmosphere and in chemically induced hypoxia. We revealed that Rmt5 interacts with post-transcriptional gene regulators, such as RNA-binding proteins and translation factors. Further investigation of the rmt5∆ mutant showed that Rmt5 is critical for the homeostasis of eIF2α and its phosphorylation state following 3-amino-1,2,4-triazole-induced ribosome stalling. RNA sequencing of one rmt5∆ clone revealed stable chromosome 9 aneuploidy that was ameliorated by complementation but did not impact the rmt5∆ phenotype. As a result of these diverse interactions and functions, loss of RMT5 enhanced phagocytosis by murine macrophages and attenuated disease progression in mice. Taken together, our findings link arginine methylation to critical cryptococcal cellular processes that impact pathogenesis, including post-transcriptional gene regulation by RNA- binding proteins.

An Interview with Mansi Srivastava

Mansi Srivastava is a John L. Loeb Associate Professor of the Natural Sciences at Harvard University. This year, she was awarded the Elizabeth D. Hay New Investigator Award by the Society of Developmental Biology, which recognizes new group leaders who have performed outstanding research in developmental biology during the early stages of their independent career. Mansi's research focusses on investigating wound response and stem cell biology during regeneration in an evolutionary context. We talked to Mansi to discover how she feels about receiving this award, and about her career and her activities outside of the lab.

A profile of research on the parasitic trypanosomatids and the diseases they cause

The parasitic trypanosomatids cause lethal and debilitating diseases, the leishmaniases, Chagas disease, and the African trypanosomiases, with major impacts on human and animal health. Sustained research has borne fruit by assisting efforts to reduce the burden of disease and by improving our understanding of fundamental molecular and cell biology. But where has the research primarily been conducted, and which research areas have received the most attention? These questions are addressed below using publication and citation data from the past few decades.

A Liquid State Perspective on Dynamics of Chromatin Compartments

The interior of the eukaryotic cell nucleus has a crowded and heterogeneous environment packed with chromatin polymers, regulatory proteins, and RNA molecules. Chromatin polymer, assisted by epigenetic modifications, protein and RNA binders, forms multi-scale compartments which help regulate genes in response to cellular signals. Furthermore, chromatin compartments are dynamic and tend to evolve in size and composition in ways that are not fully understood. The latest super-resolution imaging experiments have revealed a much more dynamic and stochastic nature of chromatin compartments than was appreciated before. An emerging mechanism explaining chromatin compartmentalization dynamics is the phase separation of protein and nucleic acids into membraneless liquid condensates. Consequently, concepts and ideas from soft matter and polymer systems have been rapidly entering the lexicon of cell biology. In this respect, the role of computational models is crucial for establishing a rigorous and quantitative foundation for the new concepts and disentangling the complex interplay of forces that contribute to the emergent patterns of chromatin dynamics and organization. Several multi-scale models have emerged to address various aspects of chromatin dynamics, ranging from equilibrium polymer simulations, hybrid non-equilibrium simulations coupling protein binding and chromatin folding, and mesoscopic field-theoretic models. Here, we review these emerging theoretical paradigms and computational models with a particular focus on chromatin’s phase separation and liquid-like properties as a basis for nuclear organization and dynamics.

Basic Concept of Cell: A Narrative Review

All body functions depend on cell integrity. Therefore, understanding cell biology is intrinsically important for understanding disease. A vast amount of information reveals how the cell behaves like an organism with many social cells. At the heart of cell biology is cell communication—how messages originate and are transmitted, received, interpreted, and used by cells. This efficient communication between, and within the cell maintains the function of the cell and its specialization. Intercellular signals enable each cell to determine its position and specific role. Cells must demonstrate a "chemical preference" for other cells and the environment that surrounds them to maintain the integrity of the whole organism. When they no longer tolerate this preference, the conversation ends and the cell adapts (sometimes changes in function) or becomes vulnerable to isolation, injury, illness, or even death. This review explains the function of each component in the cell and its role in life.

Identifying temporal and spatial patterns of variation from multimodal data using MEFISTO

Factor analysis is a widely used method for dimensionality reduction in genome biology, with applications from personalized health to single-cell biology. Existing factor analysis models assume independence of the observed samples, an assumption that fails in spatio-temporal profiling studies. Here we present MEFISTO, a flexible and versatile toolbox for modeling high-dimensional data when spatial or temporal dependencies between the samples are known. MEFISTO maintains the established benefits of factor analysis for multimodal data, but enables the performance of spatio-temporally informed dimensionality reduction, interpolation, and separation of smooth from non-smooth patterns of variation. Moreover, MEFISTO can integrate multiple related datasets by simultaneously identifying and aligning the underlying patterns of variation in a data-driven manner. To illustrate MEFISTO, we apply the model to different datasets with spatial or temporal resolution, including an evolutionary atlas of organ development, a longitudinal microbiome study, a single-cell multi-omics atlas of mouse gastrulation and spatially resolved transcriptomics.