Biology subjects

Kaiser, C.

Publications and source records attributed to Kaiser, C..

3 recordsLinked to original sources

bioRxiv2023

AP profiling resolves co-translational folding pathway and chaperone interactions in vivo

Natural proteins have evolved to fold robustly along specific pathways. Folding begins during synthesis, guided by interactions of the nascent protein with the ribosome and molecular chaperones. However, the timing and progression of co-translational folding remain largely elusive, in part because the process is difficult to measure in the natural environment of the cytosol. We developed a high-throughput method to quantify co-translational folding in live cells that we term Arrest Peptide profiling (AP profiling). We employed AP profiling to delineate co-translational folding for a set of GTPase domains with very similar structures, defining how topology shapes folding pathways. Genetic ablation of major nascent chain-binding chaperones resulted in localized folding changes that suggest how functional redundancies among chaperones are achieved by distinct interactions with the nascent protein. Collectively, our studies provide a window into cellular folding pathways of complex proteins and pave the way for systematic studies on nascent protein folding at unprecedented resolution and throughput.

molecular biology↗

bioRxiv2022

Inflammation drives age-induced loss of tissue resident macrophages

Low-grade chronic systemic inflammation, or inflammageing, is a hallmark of ageing and a risk factor for both morbidity and mortality in elderly people. Resident macrophages are tissue homeostasis sentinels that are embedded in their tissue of residence since embryonic development, thus been exposed to cumulative tissue insults throughout life. Therefore, resident macrophages, among other immune cells, emerge as potential key contributors to age-associated tissue dysfunction. Contrary to what is currently postulated, we demonstrate here that the pool of embryo-derived resident macrophages exhibits an age-dependent depletion in liver, and other solid organs and that they are not replaced by Hematopoietic Stem Cell (HSCs)-derived monocytes throughout life. Further, we demonstrate that gradual, cumulative inflammation during ageing induces this specific loss of tissue resident macrophages. Preserving a "youthful" density of resident macrophages attenuates classical hallmarks of liver age-associated dysfunction. SummaryThe pool of embryo-derived resident macrophages dwindles with age in most tissues, without compensation from Hematopoietic Stem Cell (HSC)-derived cells. This loss is not due to impaired self-renewal in old tissues but rather to increased cell death, which is driven by sustained inflammation. Attenuating inflammation sensing during ageing prevents age-induce macrophage loss and improves hallmarks of liver ageing.

immunology↗

bioRxiv2021

From Diversity to Complexity: Microbial Networks in Soils

Network analysis has been used for many years in ecological research to analyze organismal associations, for example in food webs, plant-plant or plant-animal interactions. Although network analysis is widely applied in microbial ecology, only recently has it entered the realms of soil microbial ecology, shown by a rapid rise in studies applying co-occurrence analysis to soil microbial communities. While this application offers great potential for deeper insights into the ecological structure of soil microbial ecosystems, it also brings new challenges related to the specific characteristics of soil datasets and the type of ecological questions that can be addressed. In this Perspectives Paper we assess the challenges of applying network analysis to soil microbial ecology due to the small-scale heterogeneity of the soil environment and the nature of soil microbial datasets. We review the different approaches of network construction that are commonly applied to soil microbial datasets and discuss their features and limitations. Using a test dataset of microbial communities from two depths of a forest soil, we demonstrate how different experimental designs and network constructing algorithms affect the structure of the resulting networks, and how this in turn may influence ecological conclusions. We will also reveal how assumptions of the construction method, methods of preparing the dataset, and definitions of thresholds affect the network structure. Finally, we discuss the particular questions in soil microbial ecology that can be approached by analyzing and interpreting specific network properties. Targeting these network properties in a meaningful way will allow applying this technique not in merely descriptive, but in hypothesis-driven research.

ecology↗