Mouse germline cysts, on average, develop into six oocytes supported by 24 nurse cells that transfer cyto-plasm and organelles to generate a Balbiani body. We showed that between E14.5 and P5, cysts periodically activate some nurse cells to begin cytoplasmic transfer, which causes them to shrink and turnover within 2 days. Nurse cells die by a programmed cell death (PCD) pathway involving acidification, similar to Drosophila nurse cells, and only infrequently by apoptosis. Prior to initiating transfer, nurse cells co-cluster by scRNA-seq with their pro-oocyte sisters, but during their final 2 days, they cluster separately. The genes promoting oocyte development and nurse cell PCD are upregulated, whereas the genes that repress transfer, such as Tex14, and oocyte factors, such as Nobox and Lhx8, are under-expressed. The transferred nurse cell centrosomes build a cytocentrum that establishes a large microtubule aster in the primordial oocyte that or-ganizes the Balbiani body, defining the earliest oocyte polarity.

The concept of genetic epistasis defines an interaction between two genetic loci as the degree of non-additivity in their phenotypes. A fitness landscape describes the phenotypes over many genetic loci, and the shape of this landscape can be used to predict evolutionary trajectories. Epistasis in a fitness landscape makes prediction of evolutionary trajectories more complex because the interactions between loci can produce local fitness peaks or troughs, which changes the likelihood of different paths. While various mathematical frameworks have been proposed to investigate properties of fitness landscapes, Beerenwinkel et al. (Stat Sin 17(4):1317-1342, 2007a) suggested studying regular subdivisions of convex polytopes. In this sense, each locus provides one dimension, so that the genotypes form a cube with the number of dimensions equal to the number of genetic loci considered. The fitness landscape is a height function on the coordinates of the cube. Here, we propose cluster partitions and cluster filtrations of fitness landscapes as a new mathematical tool, which provides a concise combinatorial way of processing metric information from epistatic interactions. Furthermore, we extend the calculation of genetic interactions to consider interactions between microbial taxa in the gut microbiome of Drosophila fruit flies. We demonstrate similarities with and differences to the previous approach. As one outcome we locate interesting epistatic information on the fitness landscape where the previous approach is less conclusive.

Gut bacteria can affect key aspects of host fitness, such as development, fecundity, and lifespan, while the host, in turn, shapes the gut microbiome. However, it is unclear to what extent individual species versus community interactions within the microbiome are linked to host fitness. Here, we combinatorially dissect the natural microbiome of Drosophila melanogaster and reveal that interactions between bacteria shape host fitness through life history tradeoffs. Empirically, we made germ-free flies colonized with each possible combination of the five core species of fly gut bacteria. We measured the resulting bacterial community abundances and fly fitness traits, including development, reproduction, and lifespan. The fly gut promoted bacterial diversity, which, in turn, accelerated development, reproduction, and aging: Flies that reproduced more died sooner. From these measurements, we calculated the impact of bacterial interactions on fly fitness by adapting the mathematics of genetic epistasis to the microbiome. Development and fecundity converged with higher diversity, suggesting minimal dependence on interactions. However, host lifespan and microbiome abundances were highly dependent on interactions between bacterial species. Higher-order interactions (involving three, four, and five species) occurred in 13-44% of possible cases depending on the trait, with the same interactions affecting multiple traits, a reflection of the life history tradeoff. Overall, we found these interactions were frequently context-dependent and often had the same magnitude as individual species themselves, indicating that the interactions can be as important as the individual species in gut microbiomes.

Cell- and tissue-level processes often occur across days or weeks, but few imaging methods can capture such long timescales. Here, we describe Bellymount, a simple, noninvasive method for longitudinal imaging of the Drosophila abdomen at subcellular resolution. Bellymounted animals remain live and intact, so the same individual can be imaged serially to yield vivid time series of multiday processes. This feature opens the door to longitudinal studies of Drosophila internal organs in their native context. Exploiting Bellymount's capabilities, we track intestinal stem cell lineages and gut microbial colonization in single animals, revealing spatiotemporal dynamics undetectable by previously available methods.

Predicting antibiotic efficacy within microbial communities remains highly challenging. Interspecies interactions can impact antibiotic activity through many mechanisms, including alterations to bacterial physiology. Here, we studied synthetic communities constructed from the core members of the fruit fly gut microbiota. Co-culturing of Lactobacillus plantarum with Acetobacter species altered its tolerance to the transcriptional inhibitor rifampin. By measuring key metabolites and environmental pH, we determined that Acetobacter species counter the acidification driven by L. plantarum production of lactate. Shifts in pH were sufficient to modulate L. plantarum tolerance to rifampin and the translational inhibitor erythromycin. A reduction in lag time exiting stationary phase was linked to L. plantarum tolerance to rifampicin, opposite to a previously identified mode of tolerance to ampicillin in E. coli. This mechanistic understanding of the coupling among interspecies interactions, environmental pH, and antibiotic tolerance enables future predictions of growth and the effects of antibiotics in more complex communities.

Cilia and flagella are ideal model organelles in which to study the general question of organelle size control. Flagellar microtubules are steady-state structures whose size is set by the balance of assembly and disassembly. Assembly requires intraflagellar transport (IFT), and measurements of IFT have shown that the rate of entry of IFT particles into the flagellum is a decreasing function of length. It has been proposed that this length dependence of IFT may be the basis for flagellar length control. Here, we test this idea by showing that three different long-flagella mutations in Chlamydomonas all cause increased IFT injection, thus confirming that IFT can influence length control. However, quantitative comparisons with mathematical models suggest that the increase in injection is not sufficient to explain the full increase in length seen in these mutants; hence, some other mechanism may be at work. One alternative mechanism that has been proposed is length-regulated binding of tubulin to the IFT particles. However, we find that the apparent length dependence of tubulin loading that has previously been reported may actually reflect length-dependent organization of IFT trains. This article is part of the Theo Murphy meeting issue 'Unity and diversity of cilia in locomotion and transport'.

Augmenting the genetic diversity of small, inbred populations by the introduction of new individuals is often termed "genetic rescue". An example is the Norwegian Lundehund, a small spitz dog with inbreeding-related health problems that is being crossed with three Nordic breeds, including the Norwegian Buhund. Conservation breeding decisions for the (typically) small number of outcrossed individuals are vital for managing the rescue process, and we genotyped the Lundehund (n = 12), the Buhund (n = 12), their crosses (F1, n = 7) and first-generation backcrosses to the Lundehund (F2, n = 12) with >170,000 single nucleotide polymorphism loci to compare their levels of genetic diversity. We predicted that genome-wide diversity in F2 dogs would be higher than in the Lundehund but lower than in the F1 and the Buhund, and the heterozygosity values showed the expected patterns. We also found that runs of homozygosity, extended chromosomal regions of homozygous genotypes inherited from a common ancestor, were reduced in F2 individuals compared with Lundehund individuals. Our analyses demonstrate the benefits of outcrossing but indicate that some of the acquired genetic diversity is lost following immediate backcrossing. Additional breeding among F2 crosses could therefore merit from further consideration in genetic rescue management.

Observational studies reveal substantial variability in microbiome composition across individuals. Targeted studies in gnotobiotic animals underscore this variability by showing that some bacterial strains colonize deterministically, while others colonize stochastically. While some of this variability can be explained by external factors like environmental, dietary, and genetic differences between individuals, in this paper we show that for the model organism Drosophila melanogaster, interactions between bacteria can affect the microbiome assembly process, contributing to a baseline level of microbiome variability even among isogenic organisms that are identically reared, housed, and fed. In germ free flies fed known combinations of bacterial species, we find that some species colonize more frequently than others even when fed at the same high concentration. We develop an ecological technique that infers the presence of interactions between bacterial species based on their colonization odds in different contexts, requiring only presence/absence data from two-species experiments. We use a progressive sequence of probabilistic models, in which the colonization of each bacterial species is treated as an independent stochastic process, to reproduce the empirical distributions of colonization outcomes across experiments. We find that incorporating context-dependent interactions substantially improves the performance of the models. Stochastic, context dependent microbiome assembly underlies clinical therapies like fecal microbiota transplantation and probiotic administration and should inform the design of synthetic fecal transplants and dosing regimes.