A fundamental goal of microbial ecology is to understand what determines the diversity, stability, and structure of microbial ecosystems. The microbial context poses special conceptual challenges because of the strong mutual influences between the microbes and their chemical environment through the consumption and production of metabolites. By analyzing a generalized consumer resource model that explicitly includes cross-feeding, stochastic colonization, and thermodynamics, we show that complex microbial communities generically exhibit a transition as a function of available energy fluxes from a “resource-limited” regime where community structure and stability is shaped by energetic and metabolic considerations to a diverse regime where the dominant force shaping microbial communities is the overlap between species’ consumption preferences. These two regimes have distinct species abundance patterns, different functional profiles, and respond differently to environmental perturbations. Our model reproduces large-scale ecological patterns observed across multiple experimental settings such as nestedness and differential beta diversity patterns along energy gradients. We discuss the experimental implications of our results and possible connections with disorder-induced phase transitions in statistical physics.

Surveys of microbial biodiversity such as the Earth Microbiome Project (EMP) and the Human Microbiome Project (HMP) have revealed robust ecological patterns across different environments.A major goal in ecology is to leverage these patterns to identify the ecological processes shaping microbial ecosystems. One promising approach is to use minimal models that can relate mechanistic assumptions at the microbe scale to community-level patterns. Here, we demonstrate the utility of this approach by showing that the Microbial Consumer Resource Model (MiCRM) -a minimal model for microbial communities with resource competition, metabolic crossfeeding and stochastic colonization -can qualitatively reproduce patterns found in survey data including compositional gradients, dissimilarity/overlap correlations, richness/harshness correlations, and nestedness of community composition. By using the MiCRM to generate synthetic data with different environmental and taxonomical structure, we show that large scale patterns in the EMP can be reproduced by considering the energetic cost of surviving in harsh environments and HMP patterns may reflect the importance of environmental filtering in shaping competition. We also show that recently discovered dissimilarity-overlap correlations in the HMP likely arise from communities that share similar environments rather than reflecting universal dynamics. We identify ecologically meaningful changes in parameters that alter or destroy each one of these patterns, suggesting new mechanistic hypotheses for further investigation. These findings highlight the promise of minimal models for microbial ecology. *

Magnetic exchange driven proximity effect at a magnetic-insulator-topological-insulator (MI-TI) interface provides a rich playground for novel phenomena as well as a way to realize low energy dissipation quantum devices. Here we report a dramatic enhancement of proximity exchange coupling in the MI/magnetic-TI EuS=Sb 2−x V x Te 3 hybrid heterostructure, where V doping is used to drive the TI (Sb 2 Te 3 ) magnetic. We observe an artificial antiferromagneticlike structure near the MI-TI interface, which may account for the enhanced proximity coupling. The interplay between the proximity effect and doping in a hybrid heterostructure provides insights into the engineering of magnetic ordering. The time-reversal symmetry (TRS) breaking and surface band gap opening of a topological insulator (TI) are essential ingredients necessary for towards the observation of novel quantum phases and realization for TI-based devices [1,2]. In general, there are two approaches to break the TRS: transitional-metal (TM) ion doping [3][4][5] and magnetic proximity effect where a magnetic insulator (MI) adlayer induces exchange coupling [3,[6][7][8]. Doping TM impurities into a TI will introduce a perpendicular ferromagnetic (FM) anisotropy and provide a straightforward means to open up the band gap of a TI's surface state, with profound influence to its electronic structure [4,[9][10][11][12][13][14]. In particular, quantum anomalous Hall effect (QAHE), where quantum Hall plateau and dissipationless chiral edge channels emerge at zero external magnetic field, has recently been realized in Cr-doped and V-doped TIs [9,10,[15][16][17][18][19][20]. Ideally, compared to the doping method, proximity effect has a number of advantages, including spatially uniform magnetization, better controllability of surface state, freedom from dopant-induced scattering, as well as preserving TI intrinsic crystalline structure, etc. [21,22]. However, due to the inplane anisotropy and low Curie temperature, such MIs are usually too weak to induce strong proximity magnetism in a TI. In fact, compared to a magnetically doped TI which can induce as large as a 50 meV surface band gap [4], the EuS-TI system has only a 7 meV gap opening due to the strongly localized Eu f orbitals [23]. Therefore, the enhancement of proximity magnetism is highly desirable to make it a valuable approach as doping hence takes full advantage.In this Letter, we report significant enhancement of the proximity effect in MI EuS/magnetic-TI Sb 2−x V x Te 3 hybrid heterostructure. Using polarized neutron reflectometry (PNR), we inferred an increase of proximity magnetization per unit cell (u.c.) in TI, from 1.2μ B =u:c. to 2.7μ B =u:c. at x ¼ 0.1 doping level. High-resolution transmission electron microscopy (HRTEM) identifies the TI-EuS interfacial sharpness and excludes the false positive magnetism signal from interdiffused Eu ions into a TI. Furthermore, the proximity effect enhancement is accompanied by a decrease of the interfacial magnetization of EuS, resulting in an exotic antiferro...

Living systems regulate many aspects of their behaviour through periodic oscillations of molecular concentrations, which function as ‘biochemical clocks.’ The chemical reactions that drive these clocks are intrinsically stochastic at the molecular level, so that the duration of a full oscillation cycle is subject to random fluctuations. Their success in carrying out their biological function is thought to depend on the degree to which these fluctuations in the cycle period can be suppressed. Biochemical oscillators also require a constant supply of free energy in order to break detailed balance and maintain their cyclic dynamics. For a given free energy budget, the recently discovered ‘thermodynamic uncertainty relation’ yields the magnitude of period fluctuations in the most precise conceivable free-running clock. In this paper, we show that computational models of real biochemical clocks severely underperform this optimum, with fluctuations several orders of magnitude larger than the theoretical minimum. We argue that this suboptimal performance is due to the small number of internal states per molecule in these models, combined with the high level of thermodynamic force required to maintain the system in the oscillatory phase. We introduce a new model with a tunable number of internal states per molecule and confirm that it approaches the optimal precision as this number increases.