Biology subjects

Kruithoff, R.

Publications and source records attributed to Kruithoff, R..

6 recordsLinked to original sources

bioRxiv2026

Stochastic colonization and host-to-host transmission shape gut bacterial variability

Understanding the kinetic processes that govern bacterial population dynamics within hosts is critical in developing effective strategies to control microbiota. However, inferring population dynamics is challenging due to large host-to-host bacterial population variability stemming from stochastic colonization events, as well as the inability to continuously monitor the bacterial population without disturbing the host. Using C. elegans fed E. coli under different diets, we show that early colonization acts as a stochastic bottleneck that drives substantial divergence in host-level bacterial loads, and that the spreading of bacteria from colonized worms to sterile ones regulates this variability by altering effective colonization pressure. These conclusions are reinforced using a simulation-based inference framework that quantifies stochastic within-host population dynamics from discrete snapshot data, enabling inference of effective colonization and growth rates across heterogeneous hosts with variable carrying capacities. Applying this framework, we further demonstrate that the bacterial predator B. bacteriovorus reduces average gut bacterial loads by two orders of magnitude, primarily by suppressing environmental recolonization and subsequent host-to-host transmission rather than eliminating established intra-host populations. Together, these results reveal that host-associated microbial population dynamics are strongly impacted by environmental colonization processes that modulate stochastic entry events.

microbiology↗

bioRxiv2025

GPU-accelerated, self-optimizing processing for 3D multiplexed iterative RNA-FISH experiments

Imaging-based spatial transcriptomic approaches rely on iterative labeling and imaging of carefully prepared samples, followed by solving a computational inverse problem to determine the location and identity of the targeted RNA. Because these approaches require high-resolution optics, the Nyquist-Shannon determined voxel size is small relative to typical tissue sample footprints. A common solution to speed up both experiments and computation is to increase the distance in between focal planes, trading off local information content to sample a larger imaging area in a reasonable time. In this work we introduce a GPU-accelerated computational framework, merfish3d-analysis, designed to speed up the computational processing of barcoded, in situ imaging-based spatial transcriptomics. Using this framework, we quantify the information lost due to axial sampling changes in simulated imaging-based spatial transcriptomic experiments, robustly reprocess publicly available multiplexed error-robust fluorescence in situ hybridization (MERFISH) datasets, and analyze new MERFISH experiments performed on a post-mortem human olfactory bulb sample. To improve the quality of experimental data in the post-mortem human sample, we designed a multi-step autofluorescence quenching protocol specific for in situ imaging-based spatial transcriptomic strategies. Taken together, we hope that the sample preparation protocols and single workstation, GPU-accelerated processing will further democratize imaging-based spatial transcriptomic experiments.

bioinformatics↗

bioRxiv2025

REPOP: bacterial population quantification from platecounts

Bacterial counts from native environments, such as soil or the animal gut, often show substantial variability across replicate samples. This heterogeneity is typically attributed to genetic or environmental factors. A common approach to estimating bacterial populations involves successive dilution and plating, followed by multiplying colony counts by dilution factors. This method, however, overestimates the heterogeneity in bacterial population because it conflates the inherent uncertainty in drawing a subsample from the total population with the uncertainty in the sample arising from biological origins. In other words, this approach may obscure features that may otherwise be present in the data hinting at the presence of genuine subpopulations. For example, in plate counting applied to C. elegans gut microbiota, observed multimodality is often interpreted as large host-to-host variance, while the randomness introduced by measurement is frequently ignored. To explicitly account for the uncertainty introduced by dilution and plating randomness, we introduce REPOP, a PyTorch-based library to REconstruct POpulations from Plates within a Bayesian framework. Beyond simple cases, REPOP addresses more complex scenarios, including multimodal populations and correcting the mathematically subtle, but experimentally relevant, bias introduced by excluding plates deemed too crowded to distinguish individual colonies. We demonstrate REPOPs ability to resolve distinct population peaks otherwise obscured by standard multiplication methods. Applications to both simulated and experimental datasets, including bacterial samples of different concentrations and ones from the gut microbiota of C. elegans, show that REPOP accurately recovers the underlying multimodality by properly accounting for error propagation, where naive multiplication fails. REPOP is available on GitHub: https://github.com/LabPresse/REPOP.

microbiology↗

bioRxiv2023

A Structured Illumination Microscopy Framework with Spatial-Domain Noise Propagation.

Biological images captured by microscopes are characterized by heterogeneous signal-to-noise ratios (SNRs) due to spatially varying photon emission across the field of view convoluted with camera noise. State-of-the-art unsupervised structured illumination microscopy (SIM) reconstruction algorithms, commonly implemented in the Fourier domain, do not accurately model this noise and suffer from high-frequency artifacts, user-dependent choices of smoothness constraints making assumptions on biological features, and unphysical negative values in the recovered fluorescence intensity map. On the other hand, supervised methods rely on large datasets for training, and often require retraining for new sample structures. Consequently, achieving high contrast near the maximum theoretical resolution in an unsupervised, physically principled, manner remains an open problem. Here, we propose Bayesian-SIM (B-SIM), an unsupervised Bayesian framework to quantitatively reconstruct SIM data, rectifying these shortcomings by accurately incorporating known noise sources in the spatial domain. To accelerate the reconstruction process, we use the finite extent of the point-spread-function to devise a parallelized Monte Carlo strategy involving chunking and restitching of the inferred fluorescence intensity. We benchmark our framework on both simulated and experimental images, and demonstrate improved contrast permitting feature recovery at up to 25% shorter length scales over state-of-the-art methods at both high- and low-SNR. B-SIM enables unsupervised, quantitative, physically accurate reconstruction without the need for labeled training data, democratizing high-quality SIM reconstruction and expands the capabilities of live-cell SIM to lower SNR, potentially revealing biological features in previously inaccessible regimes.

biophysics↗

bioRxiv2020

Multicolor structured illumination microscopy and quantitative control of coherent light with a digital mirror device

Structured illumination microscopy (SIM) is a broadly applicable super-resolution microscopy technique which does not impose photophysics requirements on fluorescent samples. Multicolor SIM implementations typically rely on liquid crystal on silicon (LCoS) spatial light modulators (SLMs) for precise patterning of the excitation light, but digital micromirror devices (DMDs) are a promising alternative, owing to their lower cost, increased imaging rate, and simplified experimental timings. Given these advantages, why do existing DMD SIM implementations either rely on incoherent projection, resulting in an order of magnitude lower signal-to-noise, or utilize coherent light at only a single wavelength? The primary obstacle to realizing a multicolor coherent DMD SIM microscope is the lack of an efficient approach for dealing with the blazed grating effect. To address this challenge, we developed quantitative tools applicable to a single DMD acting as a polychromatic diffractive optic. These include a closed form solution of the blaze and diffraction conditions, a forward model of DMD diffraction, and a forward model of coherent pattern projection. We applied these to identify experimentally feasible configurations using a single DMD as a polychromatic diffractive optic for combinations of three and four common fluorophore wavelengths. Based on these advances, we constructed a DMD SIM microscope for coherent light which we used to validate these models, develop a high-resolution optical transfer function measurement technique, and demonstrate SIM resolution enhancement for calibration samples, fixed cells, and live cells. This low-cost setup opens the door to applying DMDs in polychromatic applications which were previously restricted to LCoS SLMs.

biophysics↗

bioRxiv2020

A Single-Objective Light-Sheet Microscope with 200 nm-Scale Resolution.

We present an Oblique Plane Microscope that uses a bespoke glass-tipped tertiary objective to improve the resolution, field of view, and usability over previous variants. Owing to its high numerical aperture optics, this microscope achieves lateral and axial resolutions that are comparable to the square illumination mode of Lattice Light-Sheet Microscopy, but in a user friendly and versatile format. Given this performance, we demonstrate high-resolution imaging of clathrin-mediated endocytosis, vimentin, the endoplasmic reticulum, membrane dynamics, and Natural Killer-mediated cytotoxicity. Furthermore, we image biological phenomena that would be otherwise challenging or impossible to perform in a traditional light-sheet microscope geometry, including cell migration through confined spaces within a microfluidic device, subcellular photoactivation of Rac1, diffusion of cytoplasmic rheological tracers at a volumetric rate of 14 Hz, and large field of view imaging of neurons, developing embryos, and centimeter-scale tissue sections.

biophysics↗