Ion beam subcellular tomography, bioRxiv, 2019-02-23
Multiplexed ion beam imaging (MIBI) has been previously used to profile multiple parameters in two dimensions in single cells within tissue slices. Here, a mathematical and technical framework for three-dimensional subcellular MIBI is presented. We term the approach ion beam tomography (IBT) wherein ion beam images are acquired iteratively across successive, multiple scans and later compiled into a 3D format. For IBT, cells were imaged at 0.2-4 pA ion current across 1,000 axial scans. Consecutive subsets of ion beam images were binned over 3 to 20 slices (above and below) to create a resolved image, wherein binning was incremented one slice at a time to yield an enhanced multi-depth data without loss of depth resolution. Algorithmic deconvolution, tailored for ion beams, was then applied to the transformed ion image series using a hybrid deblurring algorithm and an ion beam current-dependent point-spread function. Three-dimensional processing was implemented by segmentation, mesh, molecular neighborhoods, and association maps. In cultured cancer cells and tissues, IBT enabled accessible visualization of three-dimensional volumetric distributions of genomic regions, RNA transcripts, and protein factors with 65-nm lateral and 5-nm axial resolution. IBT also enabled label-free elemental mapping of cells, allowing point of source cellular component measurements not possible for most optical microscopy targets. Detailed multiparameter imaging of subcellular features at near macromolecular resolution should now be made possible by the IBT tools and reagents provided here to open novel venues for interrogating subcellular biology.
biorxiv systems-biology 100-200-users 2019Necrotizing enterocolitis is preceded by increased gut bacterial replication, Klebsiella, and fimbriae-encoding bacteria that may stimulate TLR4 receptors, bioRxiv, 2019-02-23
Necrotizing enterocolitis (NEC) is a devastating intestinal disease that occurs primarily in premature infants. We performed genome-resolved metagenomic analysis of 1,163 fecal samples from premature infants to identify microbial features predictive of NEC. Features considered include genes, bacterial strain types, eukaryotes, bacteriophages, plasmids and growth rates. A machine learning classifier found that samples collected prior to NEC diagnosis harbored significantly more Klebsiella, bacteria encoding fimbriae, and bacteria encoding secondary metabolite gene clusters related to quorum sensing and bacteriocin production. Notably, replication rates of all bacteria, especially Enterobacteriaceae, were significantly higher two days before NEC diagnosis. The findings uncover biomarkers that could lead to early detection of NEC and targets for microbiome-based therapeutics.
biorxiv microbiology 200-500-users 2019Evolution-guided design of super-restrictor antiviral proteins reveals a breadth-versus-specificity tradeoff, bioRxiv, 2019-02-22
Host-virus evolutionary arms-races are driven by antagonistic interactions and often manifest as recurrent amino acid changes (i.e., positive selection) at their protein-protein interaction interfaces. Here, we investigated whether combinatorial mutagenesis of positions under positive selection in a host antiviral protein could enhance its restrictive properties. We tested ~800 variants of the human MxA protein, generated by combinatorial mutagenesis, for their ability to restrict Thogoto orthomyxovirus (THOV). We identified MxA ‘super-restrictors' with increased binding to THOV NP target protein and 10-fold higher anti-THOV restriction relative to wild-type human MxA, the most potent naturally-occurring anti-THOV restrictor identified. However, MxA super-restrictors of THOV were impaired in their restriction of influenza A virus. Our findings thus reveal a breadth-versus-specificity tradeoff that constrains the adaptive landscape of antiviral proteins.
biorxiv microbiology 0-100-users 2019Subcellular localization of drug distribution by super-resolution ion beam imaging, bioRxiv, 2019-02-22
Technologies that visualize multiple biomolecules at the nanometer scale in cells will enable deeper understanding of biological processes that proceed at the molecular scale. Current fluorescence-based methods for microscopy are constrained by a combination of spatial resolution limitations, limited parameters per experiment, and detector systems for the wide variety of biomolecules found in cells. We present here super-resolution ion beam imaging (srIBI), a secondary ion mass spectrometry approach capable of high-parameter imaging in 3D of targeted biological entities and exogenously added small molecules. Uniquely, the atomic constituents of the biomolecules themselves can often be used in our system as the tag. We visualized the subcellular localization of the chemotherapy drug cisplatin simultaneously with localization of five other nuclear structures, with further carbon elemental mapping and secondary electron visualization, down to ~30 nm lateral resolution. Cisplatin was preferentially enriched in nuclear speckles and excluded from closed-chromatin regions, indicative of a role for cisplatin in active regions of chromatin. These data highlight how multiplexed super-resolution techniques, such as srIBI, will enable studies of biomolecule distributions in biologically relevant subcellular microenvironments.
biorxiv systems-biology 200-500-users 2019The effect of environmental enrichment on behavioral variability depends on genotype, behavior, and type of enrichment, bioRxiv, 2019-02-22
Non-genetic individuality in behavior, also termed intragenotypic variability, has been observed across many different organisms. A potential cause of intragenotypic variability is sensitivity to minute environmental differences during development, even as major environmental parameters are kept constant. Animal enrichment paradigms often include the addition of environmental diversity, whether in the form of social interaction, novel objects, or exploratory opportunities. Enrichment could plausibly affect intragenotypic variability in opposing ways it could cause an increase in variability due to the increase in microenvironmental variation, or a decrease in variability due to elimination of aberrant behavior as animals are taken out of impoverished laboratory conditions. In order to test our hypothesis, we assayed five isogenic Drosophila melanogaster lines raised in control and mild enrichment conditions, and one isogenic line under both mild and intense enrichment conditions. We compared the mean and variability of six behavioral metrics between our enriched fly populations and the laboratory housing control. We found that enrichment often caused a small increase in variability across most of our behaviors, but that the ultimate effect of enrichment on both behavioral means and variabilities was highly dependent on genotype and its interaction with the particular enrichment treatment. Our results support previous work on enrichment that presents a highly variable picture of its effects on both behavior and physiology.
biorxiv genetics 100-200-users 2019A Bayesian Approach for Estimating Branch-Specific Speciation and Extinction Rates, bioRxiv, 2019-02-21
Species richness varies considerably among the tree of life which can only be explained by heterogeneous rates of diversification (speciation and extinction). Previous approaches use phylogenetic trees to estimate branch-specific diversification rates. However, all previous approaches disregard diversification-rate shifts on extinct lineages although 99% of species that ever existed are now extinct. Here we describe a lineage-specific birth-death-shift process where lineages, both extant and extinct, may have heterogeneous rates of diversification. To facilitate probability computation we discretize the base distribution on speciation and extinction rates into k rate categories. The fixed number of rate categories allows us to extend the theory of state-dependent speciation and extinction models (e.g., BiSSE and MuSSE) to compute the probability of an observed phylogeny given the set of speciation and extinction rates. To estimate branch-specific diversification rates, we develop two independent and theoretically equivalent approaches numerical integration with stochastic character mapping and data-augmentation with reversible-jump Markov chain Monte Carlo sampling. We validate the implementation of the two approaches in RevBayes using simulated data and an empirical example study of primates. In the empirical example, we show that estimates of the number of diversification-rate shifts are, unsurprisingly, very sensitive to the choice of prior distribution. Instead, branch-specific diversification rate estimates are less sensitive to the assumed prior distribution on the number of diversification-rate shifts and consistently infer an increased rate of diversification for Old World Monkeys. Additionally, we observe that as few as 10 diversification-rate categories are sufficient to approximate a continuous base distribution on diversification rates. In conclusion, our implementation of the lineage-specific birth-death-shift model in RevBayes provides biologists with a method to estimate branch-specific diversification rates under a mathematically consistent model.
biorxiv evolutionary-biology 0-100-users 2019