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Growing evidence suggests that the physical properties of the cellular microenvironment influence cell migration. However, it is not currently understood how active physical remodelling by cells affects migration dynamics. Here we report that cell clusters seeded on deformable collagen-I networks display persistent collective migration despite not showing any apparent intrinsic polarity. Clusters generate transient gradients in collagen density and alignment due to viscoelastic relaxation of the collagen networks. Combining theory and experiments, we show that crosslinking collagen networks or reducing cell cluster size results in reduced network deformation, shorter viscoelastic relaxation time and smaller gradients, leading to lower migration persistence. Traction force and Brillouin microscopy reveal asymmetries in force distributions and collagen stiffness during migration, providing evidence of mechanical cross-talk between cells and their substrate during migration. This physical model provides a mechanism for self-generated directional migration on viscoelastic substrates in the absence of internal biochemical polarity cues.

Animal genomes are parasitized by a horde of transposable elements (TEs) whose mutagenic activity can have catastrophic consequences. The piRNA pathway is a conserved mechanism to repress TE activity in the germline via a specialized class of small RNAs associated with effector Piwi proteins called piwi-associated RNAs (piRNAs). piRNAs are produced from discrete genomic regions called piRNA clusters (piCs). While piCs are generally enriched for TE sequences and the molecular processes by which they are transcribed and regulated are relatively well understood inDrosophila melanogaster, much less is known about the origin and evolution of piCs in this or any other species. To investigate piC evolution, we use a population genomics approach to compare piC activity and sequence composition across 8 geographically distant strains ofD. melanogasterwith high quality long-read genome assemblies. We perform extensive annotations of ovary piCs and TE content in each strain and test predictions of two proposed models of piC evolution. The‘de novo’model posits that individual TE insertions can spontaneously attain the status of a small piC to generate piRNAs silencing the entire TE family. The ‘trap’ model envisions large and evolutionary stable genomic clusters where TEs tend to accumulate and serves as a long-term “memory” of ancient TE invasions and produce a great variety of piRNAs protecting against related TEs entering the genome. It remains unclear which model best describes the evolution of piCs. Our analysis uncovers extensive variation in piC activity across strains and signatures of rapid birth and death of piCs in natural populations. Most TE families inferred to be recently or currently active show an enrichment of strain-specific insertions into large piCs, consistent with the trap model. By contrast, only a small subset of active LTR retrotransposon families is enriched for the formation of strain-specific piCs, suggesting that these families have an inherent proclivity to formde novopiCs. Thus, our findings support aspects of both‘de novo’and ‘trap’ models of piC evolution. We propose that these two models represent two extreme stages along an evolutionary continuum, which begins with the emergence of piCsde novofrom a few specific LTR retrotransposon insertions that subsequently expand by accretion of other TE insertions during evolution to form larger ‘trap’ clusters. Our study shows that piCs are evolutionarily labile and that TEs themselves are the major force driving the formation and evolution of piCs.

The karyotype, or number and arrangement of chromosomes, has varying levels of stability across both evolution and disease. Karyotype changes often originate from DNA breaks near the centromeres of chromosomes, which generally contain long arrays of tandem repeats or satellite DNA. Drosophila virilis possesses among the highest relative satellite abundances of studied species, with almost half its genome composed of three related 7 bp satellites. We discovered a strain of D. virilis that we infer recently underwent three independent chromosome fusion events involving the X and Y chromosomes, in addition to one subsequent fission event. Here, we isolate and characterize the four different karyotypes we discovered in this strain which we believe demonstrates remarkable genome instability. We discovered that one of the substrains with an X-autosome fusion has an X-to-Y chromosome nondisjunction rate 20 × higher than the D. virilis reference strain (21% vs 1%). Finally, we found an overall higher rate of DNA breakage in the substrain with higher satellite DNA compared to a genetically similar substrain with less satellite DNA. This suggests that satellite DNA abundance may play a role in the risk of genome instability. Overall, we introduce a novel system consisting of a single strain with four different karyotypes, which we believe will be useful for future studies of genome instability, centromere function, and sex chromosome evolution.

Unique patterns of inheritance and selection on Y chromosomes lead to the evolution of specialized gene functions. Yet characterizing the function of genes on Y chromosomes is notoriously difficult. We report CRISPR mutants in Drosophila of the Y-linked gene,WDY, which is required for male fertility.WDYmutants produce mature sperm with beating tails that can be transferred to females but fail to enter the female sperm storage organs. We demonstrate that the sperm tails ofWDYmutants beat approximately half as fast as wild-type sperm’s and that the mutant sperm do not propel themselves within the male ejaculatory duct or female reproductive tract (RT). These specific motility defects likely cause the sperm storage defect and sterility of the mutants. Regional and genotype-dependent differences in sperm motility suggest that sperm tail beating and propulsion do not always correlate. Furthermore, we find significant differences in the hydrophobicity of key residues of a putative calcium-binding domain between orthologs ofWDYthat are Y-linked and those that are autosomal. Given thatWDYappears to be evolving under positive selection, our results suggest thatWDY’s functional evolution coincides with its transition from autosomal to Y-linked inDrosophila melanogasterand its most closely related species. Finally, we show that mutants for another Y-linked gene,PRY, also show a sperm storage defect that may explain their subfertility. In contrast toWDY, PRYmutants do swim in the female RT, suggesting they are defective in yet another mode of motility, navigation, or a necessary interaction with the female RT. Overall, we provide direct evidence for the long-held presumption that protein-coding genes on the Drosophila Y regulate sperm motility.

Genomic imprinting is a parent-of-origin-specific expression phenomenon that plays fundamental roles in many biological processes. In animals, imprinting is only observed in therian mammals, with ∼200 imprinted genes known in humans and mice. The imprinting pattern in marsupials has been minimally investigated by examining orthologs to known eutherian imprinted genes. To identify marsupial-specific imprinting in an unbiased way, we performed RNA-seq studies on samples of fetal brain and placenta from the reciprocal cross progeny of two laboratory opossum stocks. We inferred allele-specific expression for >3,000 expressed genes and discovered/validated 13 imprinted genes, including three previously known imprinted genes, Igf2r, Peg10, and H19. We estimate that marsupials imprint ∼60 autosomal genes, which is a much smaller set compared with eutherians. Among the nine novel imprinted genes, three noncoding RNAs have no known homologs in eutherian mammals, while the remaining genes have important functions in pluripotency, transcription regulation, nucleolar homeostasis, and neural differentiation. Methylation analyses at promoter CpG islands revealed differentially methylated regions in five of these marsupial-specific imprinted genes, suggesting that differential methylation is a common mechanism in the epigenetic regulation of marsupial imprinting. Clustering and co-regulation were observed at marsupial imprinting loci Pou5f3-Npdc1 and Nkrfl-Ipncr2, but eutherian-type multi-gene imprinting clusters were not detected. Also differing from eutherian mammals, the brain and placenta imprinting profiles are remarkably similar in opossums, presumably due to the shared origin of these organs from the trophectoderm. Our results contribute to a fuller understanding of the origin, evolution, and mechanisms of genomic imprinting in therian mammals.

Sex peptide (SP), a seminal fluid protein of Drosophila melanogaster males, has been described as driving a virgin-to-mated switch in females, through eliciting an array of responses including increased egg laying, activity, and food intake and a decreased remating rate. While it is known that SP achieves this, at least in part, by altering neuronal signaling in females, the genetic architecture and temporal dynamics of the female’s response to SP remain elusive. We used a high-resolution time series RNA-sequencing dataset of female heads at 10 time points within the first 24 h after mating to learn about the genetic architecture, at the gene and exon levels, of the female’s response to SP. We find that SP is not essential to trigger early aspects of a virgin-to-mated transcriptional switch, which includes changes in a metabolic gene regulatory network. However, SP is needed to maintain and diversify metabolic changes and to trigger changes in a neuronal gene regulatory network. We further find that SP alters rhythmic gene expression in females and suggests that SP’s disruption of the female’s circadian rhythm might be key to its widespread effects.

Recent experiments have produced several Anopheles gambiae homing gene drives that disrupt female fertility genes, thereby eventually inducing population collapse. Such drives may be highly effective tools to combat malaria. One such homing drive, based on the zpg promoter driving CRISPR/Cas9, was able to eliminate a cage population of mosquitoes. A second version, purportedly improved upon the first by incorporating an X-shredder element (which biases inheritance towards male offspring), was similarly successful. Here, we analyze experimental data from each of these gene drives to extract their characteristics and performance parameters and compare these to previous interpretations of their experimental performance. We assess each suppression drive within an individual-based simulation framework that models mosquito population dynamics in continuous space. We find that the combined homing/X-shredder drive is actually less effective at population suppression within the context of our mosquito population model. In particular, the combined drive often fails to completely suppress the population, instead resulting in an unstable equilibrium between drive and wild-type alleles. By contrast, otherwise similar drives based on the nos promoter may prove to be more promising candidates for future development than originally thought.

A selective sweep occurs when positive selection drives an initially rare allele to high population frequency. In nature, the precise parameters of a sweep are seldom known: How strong was positive selection? Did the sweep involve only a single adaptive allele (hard sweep) or were multiple adaptive alleles at the locus sweeping at the same time (soft sweep)? If the sweep was soft, did these alleles originate from recurrent new mutations (RNM) or from standing genetic variation (SGV)? Here, we present a method based on supervised machine learning to infer such parameters from the patterns of genetic variation observed around a given sweep locus. Our method is trained on sweep data simulated with SLiM, a fast and flexible framework that allows us to generate training data across a wide spectrum of evolutionary scenarios and can be tailored towards the specific population of interest. Inferences are based on summary statistics describing patterns of nucleotide diversity, haplotype structure, and linkage disequilibrium, which are estimated across systematically varying genomic window sizes to capture sweeps across a wide range of selection strengths. We show that our method can accurately infer selection coefficients in the range 0.01 < s < 100 and classify sweep types between hard sweeps, RNM soft sweeps, and SGV soft sweeps with accuracy 69 % to 95 % depending on sweep strength. We also show that the method infers the correct sweep types at three empirical loci known to be associated with the recent evolution of pesticide resistance in Drosophila melanogaster. Our study demonstrates the power of machine learning for inferring sweep parameters from present-day genotyping samples, opening the door to a better understanding of the modes of adaptive evolution in nature.Author summaryAdaptation often involves the rapid spread of a beneficial genetic variant through the population in a process called a selective sweep. Here, we develop a method based on machine learning that can infer the strength of selection driving such a sweep, and distinguish whether it involved only a single adaptive variant (a so-called hard sweep) or several adaptive variants of independent origin that were simultaneously rising in frequency at the same genomic position (a so-called soft selective sweep). Our machine learning method is trained on simulated data and only requires data sampled from a single population at a single point in time. To address the challenge of simulating realistic datasets for training, we explore the behavior of the method under a variety of testing scenarios, including scenarios where the history of the population of interest was misspecified. Finally, to illustrate the accuracy of our method, we apply it to three known sweep loci that have contributed to the evolution of pesticide resistance in Drosophila melanogaster.

Sex Peptide, a seminal fluid protein ofD. melanogastermales, has been described as driving a virgin-to-mated switch in females, through eliciting an array of responses, including increased egg laying, activity and food intake and a decreased re-mating rate. While it is known that Sex Peptide achieves this, at least in part, by altering neuronal signaling in females, the identity of key molecular regulators that act downstream of Sex Peptide is not known. Here, we used a high-resolution time series RNA-sequencing dataset of female heads at 10 time points within the first 24 hours after mating to investigate the genetic architecture, at the gene- and exon-level, of the female’s response to Sex Peptide. We find that Sex Peptide is not essential to trigger a virgin-to-mated transcriptional switch, which involves changes in a metabolic gene regulatory network. However, Sex Peptide is needed to maintain and diversify metabolic changes and to trigger changes in a neuronal gene regulatory network. We further find that Sex Peptide might interact with the female’s circadian clock to orchestrate transcriptional changes across different regulatory networks. That a male seminal fluid protein can alter a female’s rhythmic gene expression has implications for our understanding of both reproductive and circadian behaviors.

Cell competition refers to the mechanism whereby less fit cells ("losers") are sensed and eliminated by more fit neighboring cells ("winners") and arises during many processes including intracellular bacterial infection. Extracellular matrix (ECM) stiffness can regulate important cellular functions, such as motility, by modulating the physical forces that cells transduce and could thus modulate the output of cellular competitions. Herein, we employ a computational model to investigate the previously overlooked role of ECM stiffness in modulating the forceful extrusion of infected "loser" cells by uninfected "winner" cells. We find that increasing ECM stiffness promotes the collective squeezing and subsequent extrusion of infected cells due to differential cell displacements and cellular force generation. Moreover, we discover that an increase in the ratio of uninfected to infected cell stiffness as well as a smaller infection focus size, independently promote squeezing of infected cells, and this phenomenon is more prominent on stiffer compared to softer matrices. Our experimental findings validate the computational predictions by demonstrating increased collective cell extrusion on stiff matrices and glass as opposed to softer matrices, which is associated with decreased bacterial spread in the basal cell monolayer

Recent experiments have produced severalAnopheles gambiaehoming gene drives that disrupt female fertility genes, thereby eventually inducing population collapse. Such drives may be highly effective tools to combat malaria. One such homing drive, based on thezpgpromoter driving CRISPR/Cas9, was able to eliminate a cage population of mosquitoes. A second version, purportedly improved upon the first by incorporating an X-shredder element (which biases inheritance towards male offspring), was similarly successful. Here, we re-analyze the data of each of these gene drives and suggest an alternative interpretation of their performance. We assess each suppression drive within an individual-based simulation framework that models mosquito population dynamics in continuous space. We find that the combined homing/X-shredder drive is actually less effective at population suppression within the context of our mosquito population model. In particular, the combined drive often fails to completely suppress the population, instead resulting in an unstable equilibrium between drive and wild-type alleles. By contrast, otherwise similar drives based on thenospromoter may prove to be more promising candidates for future development due to potentially superior performance.

Collective cell migration on extracellular matrix (ECM) networks is a key biological process involved in development, tissue homeostasis and diseases such as metastatic cancer. During invasion of epithelial cancers, cell clusters migrate through the surrounding stroma, which is comprised primarily of networks of collagen-I fibers. There is growing evidence that the rheological and topological properties of collagen networks can impact cell behavior and cell migration dynamics. During migration, cells exert mechanical forces on their substrate, resulting in an active remodeling of ECM networks that depends not only on the forces produced, but also on the molecular mechanisms that dictate network rheology. One aspect of collagen network rheology whose role is emerging as a crucial parameter in dictating cell behavior is network viscoelasticity. Dynamic reorganization of ECM networks can induce local changes in network organization and mechanics, which can further feed back on cell migration dynamics and cell-cell rearrangement. A number of studies, including many recent publications, have investigated the mechanisms underlying structural changes to collagen networks in response to mechanical force as well as the role of collagen rheology and topology in regulating cell behavior. In this mini-review, we explore the cause-consequence relationship between collagen network viscoelasticity and cell rearrangements at various spatiotemporal scales. We focus on structural alterations of collagen-I networks during collective cell migration and discuss the main rheological parameters, and in particular the role of viscoelasticity, which can contribute to local matrix stiffening during cell movement and can elicit changes in cell dynamics.

Amyotrophic lateral sclerosis (ALS) is a complex disease leading to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWAS) have discovered relatively few loci. We developed a machine learning approach called RefMap which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes which represents a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.

The distribution of the active pharmaceutical ingredient (API) within polymer-based controlled release drug products is a critical quality attribute (CQA). It is crucial for the development of such products, to be able to accurately characterize phase distributions in these products to evaluate performance and microstructure (Q3) equivalence. In this study, polymer, API, and porosity distributions in poly(lactic-co-glycolic acid) (PLGA) microspheres were characterized using a combination of focused ion beam scanning electron microscopy (FIB-SEM) and quantitative artificial intelligence (AI) image analytics. Through in-depth investigations of nine different microsphere formulations, microstructural CQAs were identified including the abundance, domain size, and distribution of the API, the polymer, and the microporosity. 3D models, digitally transformed from the FIB-SEM images, were reconstructed to predict controlled drug release numerically. Agreement between the in vitro release experiments and the predictions validated the image-based release modelling method. Sensitivity analysis revealed the dependence of release on the distribution and size of the API particles and the porosity within the polymeric microspheres, as captured through FIB-SEM imaging. To our knowledge, this is the first report showing that microstructural CQAs in PLGA microspheres derived from imaging can be quantitatively and predictively correlated with formulation and manufacturing parameters.

Studies of the impact of host genetics on gut microbiome composition have mainly focused on the impact of individual single nucleotide polymorphisms (SNPs) on gut microbiome composition, without considering their collective impact or the specific functions of the microbiome. To assess the aggregate role of human genetics on the gut microbiome composition and function, we apply sparse canonical correlation analysis (sCCA), a flexible, multivariate data integration method. A critical attribute of metagenome data is its sparsity, and here we propose application of a Tweedie distribution to accommodate this. We use the TwinsUK cohort to analyze the gut microbiomes and human variants of 250 individuals. Sparse CCA, or sCCA, identified SNPs in microbiome-associated metabolic traits (BMI, blood pressure) and microbiome-associated disorders (type 2 diabetes, some neurological disorders) and certain cancers. Both common and rare microbial functions such as secretion system proteins or antibiotic resistance were found to be associated with host genetics. sCCA applied to microbial species abundances found known associations such as Bifidobacteria species, as well as novel associations. Despite our small sample size, our method can identify not only previously known associations, but novel ones as well. Overall, we present a new and flexible framework for examining host-microbiome genetic interactions, and we provide a new dimension to the current debate around the role of human genetics on the gut microbiome.

Coacervation is a commonly used method for protein and peptide drug microencapsulation using biodegradable or bioresorbable polymers. However, there is a lack of literature focused on microencapsulation of small molecule drugs using coacervation techniques. In addition, the apparatus used for this microencapsulation method has not been well-described. The objectives of the present work were to: (1) establish a reliable apparatus for coacervation microencapsulation; (2) investigate the impact of the viscosity of the silicone oil used in processing on microsphere performance; and (3) develop a reproducible in vitro release testing method for minocycline hydrochloride microspheres. Minocycline hydrochloride was chosen as the model drug and two compositionally equivalent microsphere formulations were prepared via coacervation using an in-house designed glass vessel assembly with a novel in-house customized paddle to achieve a relatively homogeneous particle size distribution. The critical physicochemical properties including drug loading, particle size, and morphology of the prepared microspheres and the commercial microspheres product (Arestin) were determined. In vitro release testing of the prepared microspheres as well as of Arestin was performed using a sample-and-separate method. The method showed good reproducibility and discriminatory ability. The physicochemical properties (such as particle size) as well as the in vitro release characteristics of the prepared microspheres were determined to be sensitive to the viscosity of the silicone oil used in coacervation processing. The silicone oil with higher viscosity (1000 cSt) used during the coacervation process resulted in smaller particle sized microspheres and consequently caused a higher initial burst release. Whereas, the silicone oil with lower viscosity resulted in larger sized microspheres with low burst release and a slower drug release rate.