Rob Knight

From enrollment to sequencing: cancer microbiome methods reporting is inconsistent and incomplete

Reproducibility in microbiome research depends on transparent reporting of sample sizes and sequence counts both before and after quality control (QC) processes. This is an expectation formalized in the STORMS (Strengthening The Organization and Reporting of Microbiome Studies) checklist published in November 2021. Whether cancer microbiome studies comply with the STORMS items governing sample size, sequencing and quality control, however, remains largely unexamined. Here, we audited 67 clinical cancer microbiome studies against ten STORMS items that apply to every microbiome study, spanning participant and sample counts, laboratory processing, sequencing, bioinformatic processing and experimental controls. Nearly all studies reported their number of participants (96%) and final number of samples analyzed (97%). However, STORMS items beyond sample sizes were largely underreported, ranging from 9% to 36%. The median study reported two of these eight methods items, and 16 studies reported none. Reporting did not change measurably after STORMS was published and was unrelated to journal impact factor. Because aspects like read normalization, quality-control filtering, taxa removal, and contamination handling directly affect the end result of a cancer microbiome study, differences in how these are implemented can have critical implications for the field’s reproducibility as well as rigor at large. Resolving this issue will require buy-in from scientists, funding institutions, and journals to work together to enforce stricter standards for cancer microbiome methodology reporting.

Accessibility and surface area drive desert toad presence at artificial water sites in the Great Basin and Mojave Deserts

Artificial Water Sites (AWS) are human-made or modified water sources constructed or maintained for livestock, select wildlife game species, or other management purposes in arid environments. However, non-target species such as desert toads have been documented utilizing AWS. Because the reproductive ecology of desert toads relies on water, understanding factors explaining their presence at AWS can inform conservation practices. To address this lack of information, we examined how AWS design, spatial isolation, local terrain, and surrounding vegetation influenced toad presence in the Great Basin and Mojave Deserts. From May to June 2011, we surveyed 68 AWS for species presence of toads and quantified AWS design features and environmental variables. We detected Great Basin spadefoot toads (Spea intermontana) at 61% of Great Basin AWS and red-spotted toads (Anaxyrus punctatus) at 38% of Mojave AWS. We used generalized mixed-effects models and AIC model selection to identify the most informative variables. Top performing predictors resulted in the final model 'access height (lowest distance between water edge and ground surface) + surface area (surface area coverage of water)', which accounted for 86% of model weight. The predictor 'access height' had a significant negative association with toad presence whereas 'surface area' had a significant positive association. Spatial isolation, terrain, and vegetation predictors were not found to influence toad occurrence. Our results indicate that AWS design, specifically lower access height and increased surface area, enhances desert toad use, potentially improving amphibian habitat suitability and persistence.

Personalized whole-body modeling links gut microbiota to metabolic perturbations in Alzheimer’s disease

risk gene in healthy individuals, confirming our previous findings. In conclusion, we identified blood metabolites with known links to AD that were differentially influenced by gut microbiota in AD, and identified possible microbial drivers of these predicted shifts in host-microbiome interactions. These findings may facilitate the development of microbiome-informed treatments of AD.

Intracranial recordings in humans reveal differential contributions of medial and lateral orbitofrontal cortex to approach–avoidance decision-making

A single cortical circuit implements fast and slow visual search

How the brain produces different behaviors from a fixed anatomical substrate is a foundational question in neuroscience. The dominant account holds that behavioral flexibility requires distinct neural circuits: dedicated systems selectively recruited for different processing modes. An alternative proposes that flexibility arises not from switching between circuits, but from dynamically controlling the speed at which a shared circuit operates. Here, we test this account directly using intracranial EEG recordings from nineteen human patients performing two visual search tasks of markedly different difficulty: an easy color-singleton search and a difficult orientation search, a fast vs. slow dissociation attributed for four decades to distinct anatomical and oscillatory neural systems. We show that both search tasks recruit the same cortical regions, oscillatory frequencies, and processing hierarchy. Dynamic time warping reveals that the two neural trajectories are time-stretched versions of one another; the same temporal scaling appears within each condition between faster and slower trials, indexing response speed rather than the distinction between tasks. Alpha-band oscillations (~8-10 Hz) support this temporal scaling through two coordinated mechanisms: synchronizing activity across a posterior cortical network and phase-gating local high-frequency activity (70-150 Hz) within those regions at the same preferred phase in both conditions. These findings establish that, for the two tasks studied here, fast and slow visual search are not implemented by selecting between distinct dedicated circuits, but by adjusting the speed of a single alpha-coordinated architecture. The same principle may apply to other search tasks, and to other domains in which dual-process architectures have been invoked, a testable prediction for future studies.

Gut microbiome and metabolite profiles are associated with subsequent histologic MASH in a longitudinal mouse model

Megascale microbiome analysis with DartUniFrac

Canalesolide A, a Structurally Unique Polyhydroxy Macrolide from the Marine Cyanobacterium Okeania sp. with Potent Antitrypanosomal Activity

The discovery of structurally novel natural products remains central to expanding biologically relevant chemical space, particularly within underexplored marine metabolite classes. Herein, we report the discovery and complete structural elucidation of canalesolide A, a new polyhydroxylated macrolide isolated from the marine cyanobacterium Okeania sp. The compound was identified through an integrated workflow combining phenotypic screening against Trypanosoma brucei and LC-MS/MS-based molecular networking, enabling rapid prioritization of bioactive fractions and dereplication of known metabolite families. Spectroscopic analysis revealed that canalesolide A belongs to the bastimolide-related class of macrolides but exhibits a distinct structural architecture. Its structure was established by integrating ultrahigh-resolution NMR spectroscopy, empirical configurational analysis of polyol systems, targeted model compound synthesis, and controlled chemical degradation and derivatization. This combined strategy resolved stereochemical motifs that were inaccessible by direct analysis of the intact macrolide alone, providing a transferable approach for assigning densely oxygenated marine macrolides. Genome mining identified the putative biosynthetic gene cluster and proposed biosynthetic pathway for a bastimolide-related macrolide. Canalesolide A displays potent, low nanomolar antitrypanosomal activity against human-infective subspecies of T. brucei with rapid elimination of parasites within 1 h at 1 μM. Although moderate mammalian cytotoxicity was observed, preliminary in vivo efficacy/toxicity studies in infected mice suggest a narrow therapeutic window highlighting the need for improved selectivity. This study expands the structural and biosynthetic diversity of polyhydroxylated macrolides and establishes a generalizable framework for resolving stereochemically complex natural products.

Integrated multi-omics analysis identifies microbial and metabolic signatures and drivers of CNS autoimmunity

Multi-omics analyses of facial skin in acne identify distinct microbial and metabolic features at lesional and non-lesional sites

Effect of a complementary feeding intervention based on iron- and zinc-biofortified pearl millet on the gut microbiota in 12–18-month-old children: a randomized trial

Gram-Positive Bacteria and the Inverse Association between Farm Exposure and Childhood Asthma

Integrated multi-omics analysis identifies microbial and metabolic signatures and drivers of CNS autoimmunity 2305382

Milk intake links to higher Bifidobacterium and lower BMI specifically in lactose-intolerant adults.

Higher abundance of Faecalibacterium prausnitzii in the gut microbiome is associated with a lower risk of sepsis development among 6,372 individuals followed for 20 years

Applying Artificial Intelligence and machine learning in precision nutrition

Gut microbiota signatures linked to long-term mortality, diabetes, liver disease, and sepsis risk.

A multi-organ metabolomics atlas reveals molecular dysregulations in Alzheimer’s disease mouse models

Circulating lipids are related to longitudinal changes of ATN biomarkers for Alzheimer’s disease

Insects shape the cadaver decomposition microbiome and postmortem interval estimation accuracy