抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Cell membranes display a tremendous complexity of lipids and proteins designed to perform the functions cells require. To coordinate these functions, the membrane is able to laterally segregate its constituents. This capability is based on dynamic liquid-liquid immiscibility and underlies the raft concept of membrane subcompartmentalization. Lipid rafts are fluctuating nanoscale assemblies of sphingolipid, cholesterol, and proteins that can be stabilized to coalesce, forming platforms that function in membrane signaling and trafficking. Here we review the evidence for how this principle combines the potential for sphingolipid-cholesterol self-assembly with protein specificity to selectively focus membrane bioactivity.

/pdf/lipid-rafts-as-a-membrane-organizing-principle-3mxewaemed.pdf

Lipid Rafts As a Membrane-Organizing Principle

This ebook is the first authorized digital version of Kernighan and Ritchie's 1988 classic, The C Programming Language (2nd Ed.). One of the best-selling programming books published in the last fifty years, "K&R" has been called everything from the "bible" to "a landmark in computer science" and it has influenced generations of programmers. Available now for all leading ebook platforms, this concise and beautifully written text is a "must-have" reference for every serious programmers digital library.

As modestly described by the authors in the Preface to the First Edition, this "is not an introductory programming manual; it assumes some familiarity with basic programming concepts like variables, assignment statements, loops, and functions. Nonetheless, a novice programmer should be able to read along and pick up the language, although access to a more knowledgeable colleague will help."

The C programming language

When a molecule absorbs a photon of appropriate energy, a chain of photophysical events ensues, such as internal conversion or vibrational relaxation (loss of energy in the absence of light emission), fluorescence, intersystem crossing (from singlet state to a triplet state) and phosphorescence, as shown in the Jablonski diagram for organic molecules (Fig. 1). Each of the processes occurs with a certain probability, characterized by decay rate constants (k). It can be shown that the average length of time τ for the set of molecules to decay from one state to another is reciprocally proportional to the rate of decay: τ = 1/k. This average length of time is called the mean lifetime, or simply lifetime. It can also be shown that the lifetime of a photophysical process is the time required by a population of N electronically excited molecules to be reduced by a factor of e. Correspondingly, the fluorescence lifetime is the time required by a population of excited fluorophores to decrease exponentially to N/e via the loss of energy through fluorescence and other non-radiative processes. The lifetime of photophycal processes vary significantly from tens of femotoseconds for internal conversion1,2 to nanoseconds for fluorescence and microseconds or seconds for phosphorescence.1






Open in a separate window


Figure 1


Jablonski diagram and a timescale of photophysical processes for organic molecules.

/pdf/fluorescence-lifetime-measurements-and-biological-imaging-xfalzh4w7e.pdf

Fluorescence Lifetime Measurements and Biological Imaging

The phenomenon of protein aggregation and amyloid formation has become the subject of rapidly increasing research activities across a wide range of scientific disciplines. Such activities have been stimulated by the association of amyloid deposition with a range of debilitating medical disorders, from Alzheimer's disease to type II diabetes, many of which are major threats to human health and welfare in the modern world. It has become clear, however, that the ability to form the amyloid state is more general than previously imagined, and that its study can provide unique insights into the nature of the functional forms of peptides and proteins, as well as understanding the means by which protein homeostasis can be maintained and protein metastasis avoided.

The amyloid state and its association with protein misfolding diseases

Hyperactive Toll-like receptor (TLR) 7 signaling has long been appreciated as a driver of autoimmune disease by breaking tolerance to self-nucleic acids in mouse models1–5. Recently, mutations in TLR7 or its associated regulator UNC93B16, 7, were identified as monogenic causes of human lupus; the unifying feature of these mutations being TLR7 gain-of-function. TLR7 is an intracellular transmembrane receptor, sensing RNA breakdown products within late endosomes8, 9. Hence, its function depends on intricate transport mechanisms and membrane interactions within the endomembrane network. Whether perturbations of any of these endosome-related processes can give rise to TLR7 gain-of-function and facilitate self-reactivity has not been investigated. Here, we show that a dysregulated endosomal compartment leads to unrestricted TLR7 signaling and human lupus. The late endosomal BLOC-1-related protein complex (BORC) together with the small Arf1-like GTPase Arl8b controls TLR7 protein levels, and a direct interaction between Arl8b and Unc93b1 is required to regulate TLR7 turnover. We identified an amino acid insertion in UNC93B1 in a patient with childhood-onset lupus, which reduces the interaction with the BORC-Arl8b complex and leads to endosomal TLR7 accumulation. Therefore, a failure to control the proper progression of TLR7 through its endocytic life cycle is sufficient to break immunological tolerance to nucleic acids in humans. Our results highlight the importance of an intact endomembrane system to prevent autoimmune disease. As the cellular mechanisms restricting TLR7 signaling can be manifold, identifying and stratifying lupus patients based on a TLR7-driven pathogenesis could be a viable strategy towards a targeted therapy.

https://www.biorxiv.org/content/biorxiv/early/2023/04/03/2023.04.03.535356.full.pdf

Endosome dysfunction leads to gain-of-function TLR7 and human lupus

Segmentation of Membrane Protein Motion in the Axon Initial Segment

Actin rings form plasma membrane diffusion barriers.

Ligand binding of membrane proteins triggers many important cellular signaling events by the lateral aggregation of ligand-bound and other membrane proteins in the plane of the plasma membrane. This local clustering can lead to the co-enrichment of molecules that create an intracellular signal or bring sufficient amounts of activity together to shift an existing equilibrium towards the execution of a signaling event. In this way, clustering can serve as a cellular switch. The underlying uneven distribution and local enrichment of the signaling cluster's constituting membrane proteins can be used as a functional readout. This information is obtained by combining single-molecule fluorescence microscopy with cluster algorithms that can reliably and reproducibly distinguish clusters from fluctuations in the background noise to generate quantitative data on this complex process. Cluster analysis of single-molecule fluorescence microscopy data has emerged as a proliferative field, and several algorithms and software solutions have been put forward. However, in most cases, such cluster algorithms require multiple analysis parameters to be defined by the user, which may lead to biased results. Furthermore, most cluster algorithms neglect the individual localization precision connected to every localized molecule, leading to imprecise results. Bayesian cluster analysis has been put forward to overcome these problems, but so far, it has entailed high computational cost, increasing runtime drastically. Finally, most software is challenging to use as they require advanced technical knowledge to operate. Here we combined three advanced cluster algorithms with the Bayesian approach and parallelization in a user-friendly GUI and achieved up to an order of magnitude faster processing than for previous approaches. Our work will simplify access to a well-controlled analysis of clustering data generated by SMLM and significantly accelerate data processing. The inclusion of a simulation mode aids in the design of well-controlled experimental assays.

/pdf/an-efficient-gui-based-clustering-software-for-simulation-c3krsa9szd.pdf

Helge Ewers

Papers

Endosome dysfunction leads to gain-of-function TLR7 and human lupus

Segmentation of Membrane Protein Motion in the Axon Initial Segment

Actin rings form plasma membrane diffusion barriers.

An efficient GUI-based clustering software for simulation and Bayesian cluster analysis of single-molecule localization microscopy data

Optogenetic delivery of single molecules to the plasma membrane