Biology subjects

Kristensen, K.

Publications and source records attributed to Kristensen, K..

3 recordsLinked to original sources

bioRxiv2023

Tuning the double lipidation of salmon calcitonin to introduce a pore-like membrane translocation mechanism

A widespread strategy to increase the transport of therapeutic peptides across cellular membranes has been to attach lipid moieties to the peptide backbone (lipidation) to enhance their intrinsic membrane interaction. Efforts in vitro and in vivo investigating the correlation between lipidation characteristics and peptide membrane translocation efficiency have traditionally relied on end-point read-out assays and trial-and-error-based optimization strategies. Consequently, the molecular details of how therapeutic peptide lipidation affects its membrane permeation and translocation mechanisms remain unresolved. Here we employed salmon calcitonin as a model therapeutic peptide and synthesized nine double lipidated analogs with varying lipid chain lengths. We used single giant unilamellar vesicle (GUV) calcein influx time-lapse fluorescence microscopy to determine how tuning the lipidation length can lead to an All-or-None GUV filling mechanism, indicative of a peptide mediated pore formation. Finally, we used a GUVs-containing-inner-GUVs assay to demonstrate that only peptide analogs capable of inducing pore formation show efficient membrane translocation. Our data provided the first mechanistic details on how therapeutic peptide lipidation affects their membrane perturbation mechanism and demonstrated that fine-tuning lipidation parameters could induce an intrinsic pore-forming capability. These insights and the microscopy based workflow introduced for investigating structure-function relations could be pivotal for optimizing future peptide design strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC="FIGDIR/small/548826v1_ufig1.gif" ALT="Figure 1"> View larger version (87K): org.highwire.dtl.DTLVardef@23430org.highwire.dtl.DTLVardef@b06145org.highwire.dtl.DTLVardef@1c22579org.highwire.dtl.DTLVardef@12a56eb_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- Lipidating the therapeutic peptide salmon calcitonin alters its biophysical characteristics, including oligomer size, hydrophobicity and membrane activity. - Fluorescent microscopy of single GUVs enables the determination of peptide mediated reporter dye influx behavior as either graded or All-or-None, which is coupled to either smaller membrane perturbations or peptide pore formation. - Modulating the number of hydrocarbons constituting the lipidation moieties determines the membrane permeation mechanism. - By increasing the lipid chain length lipidated of salmon calcitonin goes from displaying smaller membrane perturbations to a peptide pore formation mechanism. - Effective membrane translocation of lipidated salmon calcitonin requires a peptide mediated pore forming mechanism.

biophysics↗

bioRxiv2020

Post-capillary venules is the locus for transcytosis of therapeutic nanoparticles to the brain.

Treatments of neurodegenerative diseases require biologic drugs to be actively transported across the blood-brain barrier (BBB). To answer outstanding questions regarding transport mechanisms, we determined how and where transcytosis occurs at the BBB. Using two-photon microscopy, we characterized the transport of therapeutic nanoparticles at all steps of delivery to the brain and at the nanoscale resolution in vivo. Transferrin receptor-targeted nanoparticles were taken up by endothelium at capillaries and venules, but not at arterioles. The nanoparticles moved unobstructed within endothelial cells, but transcytosis across the BBB occurred only at post-capillary venules, where endothelial and glial basement membranes form a perivascular space that can accommodate biologics. In comparison, transcytosis was absent in capillaries with closely apposed basement membranes. Thus, post-capillary venules, not capillaries, provide an entry point for transport of large molecules across the BBB, and targeting therapeutic agents to this locus may be an effective way for treating brain disorders. HIGHLIGHTSO_LIIntegration of drug carrier nanotechnology with two-photon microscopy in vivo C_LIO_LIReal-time nanoscale-resolution imaging of nanoparticle transcytosis to the brain C_LIO_LIDistinct trafficking pattern in the endothelium of cerebral venules and capillaries C_LIO_LIVenules, not capillaries, is the locus for brain uptake of therapeutic nanoparticles C_LI

neuroscience↗

bioRxiv2017

Modeling Zero-Inflated Count Data With glmmTMB

Ecological phenomena are often measured in the form of count data. These data can be analyzed using generalized linear mixed models (GLMMs) when observations are correlated in ways that require random effects. However, count data are often zero-inflated, containing more zeros than would be expected from the standard error distributions used in GLMMs, e.g., parasite counts may be exactly zero for hosts with effective immune defenses but vary according to a negative binomial distribution for non-resistant hosts.\n\nWe present a new R package, glmmTMB, that increases the range of models that can easily be fitted to count data using maximum likelihood estimation. The interface was developed to be familiar to users of the lme4 R package, a common tool for fitting GLMMs. To maximize speed and flexibility, estimation is done using Template Model Builder (TMB), utilizing automatic differentiation to estimate model gradients and the Laplace approximation for handling random effects. We demonstrate glmmTMB and compare it to other available methods using two ecological case studies.\n\nIn general, glmmTMB is more flexible than other packages available for estimating zero-inflated models via maximum likelihood estimation and is faster than packages that use Markov chain Monte Carlo sampling for estimation; it is also more flexible for zero-inflated modelling than INLA, but speed comparisons vary with model and data structure. Our package can be used to fit GLMs and GLMMs with or without zero-inflation as well as hurdle models. By allowing ecologists to quickly estimate a wide variety of models using a single package, glmmTMB makes it easier to find appropriate models and test hypotheses to describe ecological processes.

ecology↗