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Antibiotic treatment significantly impacts the human gut microbiota, but quantitative understanding of how antibiotics affect community diversity is lacking. Here, we build on classical ecological models of resource competition to investigate community responses to species-specific death rates, as induced by antibiotic activity or other growth-inhibiting factors such as bacteriophages. Our analyses highlight the complex dependence of species coexistence that can arise from the interplay of resource competition and antibiotic activity, independent of other biological mechanisms. In particular, we identify resource competition structures that cause richness to depend on the order of sequential application of antibiotics (non-transitivity), and the emergence of synergistic and antagonistic effects under simultaneous application of multiple antibiotics (non-additivity). These complex behaviors can be prevalent, especially when generalist consumers are targeted. Communities can be prone to either synergism or antagonism, but typically not both, and antagonism is more common. Furthermore, we identify a striking overlap in competition structures that lead to non-transitivity during antibiotic sequences and those that lead to non-additivity during antibiotic combination. In sum, our results establish a broadly applicable framework for predicting microbial community dynamics under deleterious perturbations. Antibiotics impact the gut microbiota in complex ways. Here, employing ecological models of resource competition, Newton et al. elucidate species coexistence patterns under resource competition and species-specific death rates, providing a model to predict microbiota dynamics under deleterious perturbations.

Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these macroecological patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical distribution. Our model parametrizes the consumer-resource properties of a community using only a small number of global parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We show that variation in these macroscopic parameters strongly affects the time series statistics generated by the model, and we identify specific sets of global parameters that can recapitulate macroecological patterns across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice, without needing to specify microscopic details of resource consumption. These findings suggest that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under a simple model, and provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.

Perturbations such as dietary shifts and drug treatment can reduce gut microbiome diversity, with negative consequences for host health, yet predicting diversity responses remains challenging because microbial species interact through multiple mechanisms. While nutrient competition and cross-feeding both influence microbiota assembly, environmental stresses such as antibiotics are typically studied experimentally in monoculture, and most theoretical frameworks consider nutrient competition alone. To investigate how these processes jointly shape community structure, we develop a consumer-resource model that incorporates nutrient competition, growth-inhibiting stress, and metabolite cross-feeding with a unified framework spanning varied cross-feeding architectures. For three-species communities, coexistence during narrow-spectrum growth inhibition is maximized by cyclic cross-feeding networks, whereas fully connected cross-feeding networks maximize coexistence during broad-spectrum growth inhibition. However, the benefits of cyclic cross-feeding depend strongly on community size and stress targeting: in communities with more than six species and six resources, cyclic networks can destabilize coexistence. These results are robust to inefficient leakage, dead-end metabolites, and embedding in larger communities, and large communities generalize to random leakage architectures in which connectivity determines the response to stress. Together, this framework shows that cross-feeding network architecture can fundamentally reshape how microbial communities respond to growth-inhibiting stresses. Here, the authors develop a consumer-resource model to investigate how cross-feeding shapes microbial diversity and show that cyclic networks support coexistence under narrow-spectrum stress but destabilize larger communities, while fully connected networks favor coexistence under broad-spectrum stress.

Microbial community dynamics arise through interspecies interactions, including resource competition, cross-feeding and pH modulation. The individual contributions of these mechanisms to community structure are challenging to untangle. Here we develop a framework to estimate multispecies niche overlaps by combining metabolomics data of individual species, growth measurements in spent media and mathematical models. We applied our framework to an in vitro model system comprising 15 human gut commensals in complex media and showed that a simple model of resource competition accounted for most pairwise interactions. Next, we built a coarse-grained consumer-resource model by grouping metabolomic features depleted by the same set of species and showed that this model predicted the composition of 2-member to 15-member communities with reasonable accuracy. Furthermore, we found that incorporation of cross-feeding and pH-mediated interactions improved model predictions of species coexistence. Our theoretical model and experimental framework can be applied to characterize interspecies interactions in bacterial communities in vitro. A model to predict bacterial community assembly is devised on the basis of experimental data reporting competition for resources in vitro.

Deferiprone (DFP) is a hydroxypyridinone-derived iron chelator currently in clinical use for iron chelation therapy. DFP has also been known to elicit antiproliferative activities, yet the mechanism of this effect has remained elusive. We herein report that DFP chelates the Fe 2+ ion at the active sites of selected iron-dependent histone lysine demethylases (KDMs), resulting in pan inhibition of a subfamily of KDMs. Specifically, DFP inhibits the demethylase activities of six KDMs - 2A, 2B, 5C, 6A, 7A and 7B - with low micromolar IC 50 s while considerably less active or inactive against eleven KDMs - 1A, 3A, 3B, 4A-E, 5A, 5B and 6B. The KDM that is most sensitive to DFP, KDM6A, has an IC 50 that is between 7- and 70-fold lower than the iron binding equivalence concentrations at which DFP inhibits ribonucleotide reductase (RNR) activities and/or reduces the labile intracellular zinc ion pool. In breast cancer cell lines, DFP potently inhibits the demethylation of H3K4me3 and H3K27me3, two chromatin posttranslational marks that are subject to removal by several KDM subfamilies which are inhibited by DFP in cell-free assay. These data strongly suggest that DFP derives its anti-proliferative activity largely from the inhibition of a sub-set of KDMs. The docked poses adopted by DFP at the KDM active sites enabled identification of new DFP-based KDM inhibitors which are more cytotoxic to cancer cell lines. We also found that a cohort of these agents inhibited HP1-mediated gene silencing and one lead compound potently inhibited breast tumor growth in murine xenograft models. Overall, this study identified a new chemical scaffold capable of inhibiting KDM enzymes, globally changing histone modification profiles, and with specific anti-tumor activities.

H1 linker histones facilitate higher-order chromatin folding and are essential for mammalian development. To achieve high-resolution mapping of H1 variants H1d and H1c in embryonic stem cells (ESCs), we have established a knock-in system and shown that the N-terminally tagged H1 proteins are functionally interchangeable to their endogenous counterparts in vivo. H1d and H1c are depleted from GC- and gene-rich regions and active promoters, inversely correlated with H3K4me3, but positively correlated with H3K9me3 and associated with characteristic sequence features. Surprisingly, both H1d and H1c are significantly enriched at major satellites, which display increased nucleosome spacing compared with bulk chromatin. While also depleted at active promoters and enriched at major satellites, overexpressed H1(0) displays differential binding patterns in specific repetitive sequences compared with H1d and H1c. Depletion of H1c, H1d, and H1e causes pericentric chromocenter clustering and de-repression of major satellites. These results integrate the localization of an understudied type of chromatin proteins, namely the H1 variants, into the epigenome map of mouse ESCs, and we identify significant changes at pericentric heterochromatin upon depletion of this epigenetic mark.

In nature, microorganisms exhibit different volumes spanning six orders of magnitude 1 . Despite their capability to create different sizes, a clonal population in a given environment maintains a uniform size across individual cells. Recent studies in eukaryotic and bacterial organisms showed that this homogeneity in cell size can be accomplished by growing a constant size between two cell cycle events (that is, the adder model 2 – 6 ). Demonstration of the adder model led to the hypothesis that this phenomenon is a consequence of convergent evolution. Given that archaeal cells share characteristics with both bacteria and eukaryotes, we investigated whether and how archaeal cells exhibit control over cell size. To this end, we developed a soft-lithography method of growing the archaeal cells to enable quantitative time-lapse imaging and single-cell analysis, which would be useful for other microorganisms. Using this method, we demonstrated that Halobacterium   salinarum , a hypersaline-adapted archaeal organism, grows exponentially at the single-cell level and maintains a narrow-size distribution by adding a constant length between cell division events. Interestingly, the archaeal cells exhibited greater variability in cell division placement and exponential growth rate across individual cells in a population relative to those observed in Escherichia   coli 6 – 9 . Here, we present a theoretical framework that explains how these larger fluctuations in archaeal cell cycle events contribute to cell size variability and control. Using a soft-lithography method that enables single-cell analysis of Halobacterium   salinarum , this study shows that archaeal cells achieve homogeneity in cell size by growing a constant size between two cell cycle events (that is, the adder model).

Pluripotent embryonic stem cells (ESCs) are known to possess a relatively open chromatin structure; yet, despite efforts to characterize the chromatin signatures of ESCs, the role of chromatin compaction in stem cell fate and function remains elusive. Linker histone H1 is important for higher-order chromatin folding and is essential for mammalian embryogenesis. To investigate the role of H1 and chromatin compaction in stem cell pluripotency and differentiation, we examine the differentiation of embryonic stem cells that are depleted of multiple H1 subtypes. H1c/H1d/H1e triple null ESCs are more resistant to spontaneous differentiation in adherent monolayer culture upon removal of leukemia inhibitory factor. Similarly, the majority of the triple-H1 null embryoid bodies (EBs) lack morphological structures representing the three germ layers and retain gene expression signatures characteristic of undifferentiated ESCs. Furthermore, upon neural differentiation of EBs, triple-H1 null cell cultures are deficient in neurite outgrowth and lack efficient activation of neural markers. Finally, we discover that triple-H1 null embryos and EBs fail to fully repress the expression of the pluripotency genes in comparison with wild-type controls and that H1 depletion impairs DNA methylation and changes of histone marks at promoter regions necessary for efficiently silencing pluripotency gene Oct4 during stem cell differentiation and embryogenesis. In summary, we demonstrate that H1 plays a critical role in pluripotent stem cell differentiation, and our results suggest that H1 and chromatin compaction may mediate pluripotent stem cell differentiation through epigenetic repression of the pluripotency genes.

Organisms across all domains of life regulate the size of their cells. However, the means by which this is done is poorly understood. We study two abstracted \"molecular\" models for size regulation: inhibitor dilution and initiator accumulation. We apply the models to two settings: bacteria like , that grow fully before they set a division plane and divide into two equally sized cells, and cells that form a bud early in the cell division cycle, confine new growth to that bud, and divide at the connection between that bud and the mother cell, like the budding yeast . In budding cells, delaying cell division until buds reach the same size as their mother leads to very weak size control, with average cell size and standard deviation of cell size increasing over time and saturating up to 100-fold higher than those values for cells that divide when the bud is still substantially smaller than its mother. In budding yeast, both inhibitor dilution or initiator accumulation models are consistent with the observation that the daughters of diploid cells add a constant volume before they divide. This \"adder\" behavior has also been observed in bacteria. We find that in bacteria an inhibitor dilution model produces adder correlations that are not robust to noise in the timing of DNA replication initiation or in the timing from initiation of DNA replication to cell division (the + period). In contrast, in bacteria an initiator accumulation model yields robust adder correlations in the regime where noise in the timing of DNA replication initiation is much greater than noise in the + period, as reported previously (Ho and Amir, 2015). In bacteria, division into two equally sized cells does not broaden the size distribution.

Bacteria tightly regulate and coordinate the various events in their cell cycles to duplicate themselves accurately and to control their cell sizes. Growth of Escherichia coli, in particular, follows a relation known as Schaechter’s growth law. This law says that the average cell volume scales exponentially with growth rate, with a scaling exponent equal to the time from initiation of a round of DNA replication to the cell division at which the corresponding sister chromosomes segregate. Here, we sought to test the robustness of the growth law to systematic perturbations in cell dimensions achieved by varying the expression levels of mreB and ftsZ. We found that decreasing the mreB level resulted in increased cell width, with little change in cell length, whereas decreasing the ftsZ level resulted in increased cell length. Furthermore, the time from replication termination to cell division increased with the perturbed dimension in both cases. Moreover, the growth law remained valid over a range of growth conditions and dimension perturbations. The growth law can be quantitatively interpreted as a consequence of a tight coupling of cell division to replication initiation. Thus, its robustness to perturbations in cell dimensions strongly supports models in which the timing of replication initiation governs that of cell division, and cell volume is the key phenomenological variable governing the timing of replication initiation. These conclusions are discussed in the context of our recently proposed “adder-per-origin” model, in which cells add a constant volume per origin between initiations and divide a constant time after initiation.