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Archaea, bacteria, and fungi in the soil are increasingly recognized as determinants of agricultural productivity and sustainability. A crucial step for exploring soil microbiomes with important ecosystem functions is to perform statistical analyses on the potential relationship between microbiome structure and functions based on comparisons of hundreds or thousands of environmental samples collected across broad geographic ranges. In this study, we integrated agricultural field metadata with microbial community analyses by targeting 2, 903 bulk soil samples collected along a latitudinal gradient from cool-temperate to subtropical regions in Japan (26.1–42.8 °N). The data involving 632 archaeal, 26, 868 bacterial, and 4, 889 fungal operational taxonomic units detected across the fields of 19 crop plant species allowed us to conduct statistical analyses (permutational analyses of variance, generalized linear mixed models, randomization analyses, and network analyses) on the relationship among edaphic factors, microbiome compositions, and crop disease prevalence. We then examined whether the diverse microbes form species sets varying in potential ecological impacts on crop plants. A network analysis suggested that the observed prokaryotes and fungi were classified into several species sets (network modules), which differed substantially in association with crop disease prevalence. Within the network of microbe-to-microbe coexistence, ecologically diverse microbes, such as an ammonium-oxidizing archaeon, an antibiotics-producing bacterium, and a potentially mycoparasitic fungus, were inferred to play key roles in shifts between crop-disease-promotive and crop-disease-suppressive states of soil microbiomes. The bird’s-eye view of soil microbiome structure will provide a basis for designing and managing agroecosystems with high disease-suppressive functions.

HOIL-1L deficiency was recently reported to be one of the causes of myopathy and dilated cardiomyopathy (DCM). However, the mechanisms by which myopathy and DCM develop have not been clearly elucidated. Here, we sought to elucidate these mechanisms using the murine myoblast cell line C2C12 and disease-specific human induced pluripotent stem cells (hiPSCs). Myotubes differentiated from HOIL-1L-KO C2C12 cells exhibited deteriorated differentiation and mitotic cell accumulation. CMs differentiated from patient-derived hiPSCs had an abnormal morphology with a larger size and were excessively multinucleated compared with CMs differentiated from control hiPSCs. Further analysis of hiPSC-derived CMs showed that HOIL-1L deficiency caused cell cycle alteration and mitotic cell accumulation. These results demonstrate that abnormal cell maturation possibly contribute to the development of myopathy and DCM. In conclusion, HOIL-1L is an important intrinsic regulator of cell cycle-related myotube and CM maturation and cell proliferation.

Ferroptosis is a form of regulated cell death induced by iron-dependent accumulation of lipid hydroperoxides. Selenoprotein glutathione peroxidase 4 (GPX4) suppresses ferroptosis by detoxifying lipid hydroperoxides via a catalytic selenocysteine (Sec) residue. Sec, the genetically encoded [st]21 amino acid, is biosynthesized from a reactive selenium donor on its cognate [[Ser]Sec]tRNA. It is thought that intracellular selenium must be delivered ‘safely’ and ‘efficiently’ by a carrier protein owing to its high reactivity and very low concentrations. Here, we identified peroxiredoxin 6 (PRDX6) as a novel selenoprotein synthesis factor. Loss of PRDX6 decreases the expression of selenoproteins and induces ferroptosis via a reduction in GPX4. Mechanistically, PRDX6 increases the efficiency of intracellular selenium utilization by transferring selenium between proteins within the selenocysteyl-[[Ser]Sec]tRNA synthesis machinery, leading to efficient synthesis of selenocysteyl-[[Ser]Sec]tRNA. These findings highlight previously unidentified selenium metabolic systems and provide new insights into ferroptosis.

OTULIN-related autoinflammatory syndrome (ORAS), a severe autoinflammatory disease, is caused by biallelic pathogenic variants of OTULIN, a linear ubiquitin-specific deubiquitinating enzyme. Loss of OTULIN attenuates linear ubiquitination by inhibiting the linear ubiquitin chain assembly complex (LUBAC). Here, we report a patient who harbors two rare heterozygous variants of OTULIN (p.P152L and p.R306Q). We demonstrated accumulation of linear ubiquitin chains upon TNF stimulation and augmented TNF-induced cell death in mesenchymal stem cells differentiated from patient-derived iPS cells, which confirms that the patient has ORAS. However, although the de novo p.R306Q variant exhibits attenuated deubiquitination activity without reducing the amount of OTULIN, the deubiquitination activity of the p.P152L variant inherited from the mother was equivalent to that of the wild-type. Patient-derived MSCs in which the p.P152L variant was replaced with wild-type also exhibited augmented TNF-induced cell death and accumulation of linear chains. The finding that ORAS can be caused by a dominant-negative p.R306Q variant of OTULIN furthers our understanding of disease pathogenesis.

The structure of microbiomes is often classified into discrete or semi-discrete types potentially differing in community-scale functional profiles. Elucidating the mechanisms that generate such “alternative states” of microbiome compositions has been one of the major challenges in ecology and microbiology. In a time-series analysis of experimental microbiomes, we here show that both deterministic and stochastic ecological processes drive divergence of alternative microbiome states. We introduced species-rich soil-derived microbiomes into eight types of culture media with 48 replicates, monitoring shifts in community compositions at six time points (8 media × 48 replicates × 6 time points = 2304 community samples). We then confirmed that microbial community structure diverged into a few state types in each of the eight medium conditions as predicted in the presence of both deterministic and stochastic community processes. In other words, microbiome structure was differentiated into a small number of reproducible compositions under the same environment. This fact indicates not only the presence of selective forces leading to specific equilibria of community-scale resource use but also the influence of demographic drift (fluctuations) on the microbiome assembly. A reference-genome-based analysis further suggested that the observed alternative states differed in ecosystem-level functions. These findings will help us examine how microbiome structure and functions can be controlled by changing the “stability landscapes” of ecological community compositions.