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Biomedical subjects

Rob Knight

Publications and source records attributed to Rob Knight.

At least 19 recordsLinked to original sources
PubMed2026

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.

Macrolides↗
PubMed2026

Interconnected influences of diet, gut microbiome, and metabolome on cognition across three metabolomics platforms.

Cognitive impairment is increasing with global aging, yet mechanisms linking diet, the gut microbiome, and metabolism to cognitive function remain unclear. To investigate a diet-microbiome-metabolome axis associated with cognition, we integrated fecal metagenomics, diet, and multi-platform plasma metabolomics in 505 older adults from four ADRCs. Several microbes broadly associated with circulating metabolites were also linked to multiple measures of cognitive performance. These taxa exhibited coordinated metabolic signatures, with cognition-positive microbes associated with antioxidant, lipid, and microbial-host co-metabolites, and microbes negatively associated with cognition were linked to inflammatory and aromatic amino acid-derived metabolites. Dietary patterns, particularly the Healthy Eating Index Greens and Beans component, were associated with microbial composition and metabolomic structure. Mediation analyses supported a diet-microbe-metabolite-cognition pathway, while metabolites remained associated with cognition after accounting for microbial features. These findings highlight the metabolome as a central integrator of diet, microbial activity, and cognitive function.

Journal Article↗
PubMed2025

Novel insights into the genetic architecture and mechanisms of host/microbiome interactions from a multi-cohort analysis of outbred laboratory rats.

The intestinal microbiome influences health and disease. Its composition is affected by host genetics and environmental exposures. Understanding host genetic effects is critical but challenging in humans, due to the difficulty of detecting, mapping and interpreting them. To address this, we analysed host genetic effects in four cohorts of outbred laboratory rats exposed to distinct but controlled environments. We found that polygenic host genetic effects were consistent across environments. We identified three replicated microbiome-associated loci, one of which involved a sialyltransferase gene and Paraprevotella. We found a similar association in a human cohort, between ST6GAL1 and Paraprevotella, both of which have been linked with immune and infectious diseases. Moreover, we found evidence of indirect genetic effects on microbiome phenotypes, which substantially increased their total genetic variance. Finally, we identified a novel mechanism whereby indirect genetic effects can contribute to "missing heritability".

Journal Article↗
PubMed2025

Versatile wastewater monitoring of pathogens and antimicrobial resistance enabled by metatranscriptomics and long-read metagenomics.

Widespread interest in the development of population-wide pathogen and antimicrobial resistance (AMR) monitoring has revealed wastewater's microbial footprint as a marker of public health. Near-source wastewater remains a difficult sample type for microbiome analyses but represents a closer link to human health than the downstream products of its treatment. Few studies integrate methods for non-targeted monitoring applications, and critically, current methods cannot connect AMR genes to species, nor resolve full genomes. We address these challenges by developing a pipeline that enables untargeted metagenomics, metatranscriptomics, and novel long-read metagenomics (LRG). We achieve untargeted pathogen detection, limited by highly abundant resident species, while retaining microbial information with near-source sampling. Furthermore, LRG identifies antibiotic resistance gene-containing microbes and enables assembly of culture-independent genomes with previously unreported AMR genes. We establish an integrated approach to broadly monitor pathogens in wastewater, while demonstrating the importance of LRG to illuminate microbial AMR at the species level.

Journal Article↗
PubMed2025

Microbiota and kidney disease: the road ahead.

More than 850 million individuals worldwide, accounting for 10-15% of the adult population, are estimated to have chronic kidney disease. Each of these individuals is host to tens of trillions of microorganisms that are collectively referred to as microbiota - a dynamic ecosystem that both influences host health and is itself influenced by changes in the host. Available evidence supports the existence of functional connections between resident microorganisms and kidney health that are altered in the context of specific kidney diseases, including acute kidney injury, chronic kidney disease and renal stone disease. Moreover, promising data from preclinical studies suggest that targeting of gut microbial pathways may provide new therapeutic opportunities for the treatment of kidney disease. This Roadmap describes current understanding of the mechanisms by which microorganisms regulate host organ function, the effects of kidney disease on the gut microbiome, and how these insights may contribute to the development of microbe-targeted therapeutics. We highlight key knowledge gaps that remain to be addressed and strategies for addressing these, outlining both the promise and the potential pitfalls of leveraging our understanding of the gut microbiota to better understand and treat kidney disease.

Humans↗
PubMed2007

Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities.

The assessment of microbial diversity and distribution is a major concern in environmental microbiology. There are two general approaches for measuring community diversity: quantitative measures, which use the abundance of each taxon, and qualitative measures, which use only the presence/absence of data. Quantitative measures are ideally suited to revealing community differences that are due to changes in relative taxon abundance (e.g., when a particular set of taxa flourish because a limiting nutrient source becomes abundant). Qualitative measures are most informative when communities differ primarily by what can live in them (e.g., at high temperatures), in part because abundance information can obscure significant patterns of variation in which taxa are present. We illustrate these principles using two 16S rRNA-based surveys of microbial populations and two phylogenetic measures of community beta diversity: unweighted UniFrac, a qualitative measure, and weighted UniFrac, a new quantitative measure, which we have added to the UniFrac website (http://bmf.colorado.edu/unifrac). These studies considered the relative influences of mineral chemistry, temperature, and geography on microbial community composition in acidic thermal springs in Yellowstone National Park and the influences of obesity and kinship on microbial community composition in the mouse gut. We show that applying qualitative and quantitative measures to the same data set can lead to dramatically different conclusions about the main factors that structure microbial diversity and can provide insight into the nature of community differences. We also demonstrate that both weighted and unweighted UniFrac measurements are robust to the methods used to build the underlying phylogeny.

Animals↗
PubMed2006

Using the nucleotide substitution rate matrix to detect horizontal gene transfer.

BACKGROUND: Horizontal gene transfer (HGT) has allowed bacteria to evolve many new capabilities. Because transferred genes perform many medically important functions, such as conferring antibiotic resistance, improved detection of horizontally transferred genes from sequence data would be an important advance. Existing sequence-based methods for detecting HGT focus on changes in nucleotide composition or on differences between gene and genome phylogenies; these methods have high error rates. RESULTS: First, we introduce a new class of methods for detecting HGT based on the changes in nucleotide substitution rates that occur when a gene is transferred to a new organism. Our new methods discriminate simulated HGT events with an error rate up to 10 times lower than does GC content. Use of models that are not time-reversible is crucial for detecting HGT. Second, we show that using combinations of multiple predictors of HGT offers substantial improvements over using any single predictor, yielding as much as a factor of 18 improvement in performance (a maximum reduction in error rate from 38% to about 3%). Multiple predictors were combined by using the random forests machine learning algorithm to identify optimal classifiers that separate HGT from non-HGT trees. CONCLUSION: The new class of HGT-detection methods introduced here combines advantages of phylogenetic and compositional HGT-detection techniques. These new techniques offer order-of-magnitude improvements over compositional methods because they are better able to discriminate HGT from non-HGT trees under a wide range of simulated conditions. We also found that combining multiple measures of HGT is essential for detecting a wide range of HGT events. These novel indicators of horizontal transfer will be widely useful in detecting HGT events linked to the evolution of important bacterial traits, such as antibiotic resistance and pathogenicity.

Computational Biology↗
PubMed2006

UniFrac--an online tool for comparing microbial community diversity in a phylogenetic context.

BACKGROUND: Moving beyond pairwise significance tests to compare many microbial communities simultaneously is critical for understanding large-scale trends in microbial ecology and community assembly. Techniques that allow microbial communities to be compared in a phylogenetic context are rapidly gaining acceptance, but the widespread application of these techniques has been hindered by the difficulty of performing the analyses. RESULTS: We introduce UniFrac, a web application available at http://bmf.colorado.edu/unifrac, that allows several phylogenetic tests for differences among communities to be easily applied and interpreted. We demonstrate the use of UniFrac to cluster multiple environments, and to test which environments are significantly different. We show that analysis of previously published sequences from the Columbia river, its estuary, and the adjacent coastal ocean using the UniFrac interface provided insights that were not apparent from the initial data analysis, which used other commonly employed techniques to compare the communities. CONCLUSION: UniFrac provides easy access to powerful multivariate techniques for comparing microbial communities in a phylogenetic context. We thus expect that it will provide a completely new picture of many microbial interactions and processes in both environmental and medical contexts.

Bacteria↗
PubMed2006

DivergentSet, a tool for picking non-redundant sequences from large sequence collections.

DivergentSet addresses the important but so far neglected bioinformatics task of choosing a representative set of sequences from a larger collection. We found that using a phylogenetic tree to guide the construction of divergent sets of sequences can be up to 2 orders of magnitude faster than the naive method of using a full distance matrix. By providing a user-friendly interface (available online) that integrates the tasks of finding additional sequences, building and refining the divergent set, producing random divergent sets from the same sequences, and exporting identifiers, this software facilitates a wide range of bioinformatics analyses including finding significant motifs and covariations. As an example application of DivergentSet, we demonstrate that the motifs identified by the motif-finding package MEME (Motif Elicitation by Maximum Entropy) are highly unstable with respect to the specific choice of sequences. This instability suggests that the types of sensitivity analysis enabled by DivergentSet may be widely useful for identifying the motifs of biological significance.

Amino Acid Sequence↗
PubMed2006

Fast-Find: a novel computational approach to analyzing combinatorial motifs.

BACKGROUND: Many vital biological processes, including transcription and splicing, require a combination of short, degenerate sequence patterns, or motifs, adjacent to defined sequence features. Although these motifs occur frequently by chance, they only have biological meaning within a specific context. Identifying transcripts that contain meaningful combinations of patterns is thus an important problem, which existing tools address poorly. RESULTS: Here we present a new approach, Fast-FIND (Fast-Fully Indexed Nucleotide Database), that uses a relational database to support rapid indexed searches for arbitrary combinations of patterns defined either by sequence or composition. Fast-FIND is easy to implement, takes less than a second to search the entire Drosophila genome sequence for arbitrary patterns adjacent to sites of alternative polyadenylation, and is sufficiently fast to allow sensitivity analysis on the patterns. We have applied this approach to identify transcripts that contain combinations of sequence motifs for RNA-binding proteins that may regulate alternative polyadenylation. CONCLUSION: Fast-FIND provides an efficient way to identify transcripts that are potentially regulated via alternative polyadenylation. We have used it to generate hypotheses about interactions between specific polyadenylation factors, which we will test experimentally.

Algorithms↗
PubMed2006

Natural selection is not required to explain universal compositional patterns in rRNA secondary structure categories.

We have encountered an unexpected property of rRNA secondary structures that may generalize to all RNAs. Analysis of 8892 ribosomal RNA sequences and structures from a wide range of species revealed unexpected universal compositional trends. First, different categories of rRNA secondary structure (stems, loops, bulges, and junctions) have distinct, characteristic base compositions. Second, the observed patterns of variation are similar among sequences from large and small rRNA subunits and all domains of life, despite extensive evolutionary divergence. Surprisingly, these differences do not seem to be related to selection for different compositions in different structural categories, but rather relate to the overall composition of the molecule: Randomized RNAs with no evolutionary history show the same structure-dependent compositional biases as rRNAs. These compositional trends may improve the accuracy of RNA secondary structure prediction, because they allow us to compare predicted structures against known compositional preferences. They also suggest caution in interpreting differences in the rate of change of the GC content in different parts of the molecule as evidence of differential selection.

Base Composition↗
PubMed2005

Abundance of correctly folded RNA motifs in sequence space, calculated on computational grids.

Although functional RNA molecules are known to be biased in overall composition, the effects of background composition on the probability of finding a particular active site by chance has received little attention. The probability of finding a particular motif has important implications both for understanding the distribution of functional RNAs in ancient and modern organisms with varying genome compositions and for tuning SELEX pools to optimize the chance of finding specific functions. Here we develop a new method for calculating the probability of finding a modular motif containing base-paired regions, and use a computational grid to fold several hundred million random RNA sequences containing the core elements of the isoleucine aptamer and the hammerhead ribozyme to estimate the probability that a sequence containing these structural elements will fold correctly when isolated from background sequences of different compositions. We find that the two motifs are most likely to be found in distinct regions of compositional space, and that the regions of greatest abundance are influenced by the probability of finding the conserved bases, finding the flanking helices, and folding, in that order of importance. Additionally, we can refine our estimates of the number of random sequences required for a 50% probability of finding an example of each site in unbiased random pools of length 100 to 4.1 x 10(9) for the isoleucine aptamer and 1.6 x 10(10) for the hammerhead ribozyme. These figures are consistent with the facile recovery of these motifs from SELEX experiments.

Base Composition↗
PubMed2005

Do universal codon-usage patterns minimize the effects of mutation and translation error?

BACKGROUND: Do species use codons that reduce the impact of errors in translation or replication? The genetic code is arranged in a way that minimizes errors, defined as the sum of the differences in amino-acid properties caused by single-base changes from each codon to each other codon. However, the extent to which organisms optimize the genetic messages written in this code has been far less studied. We tested whether codon and amino-acid usages from 457 bacteria, 264 eukaryotes, and 33 archaea minimize errors compared to random usages, and whether changes in genome G+C content influence these error values. RESULTS: We tested the hypotheses that organisms choose their codon usage to minimize errors, and that the large observed variation in G+C content in coding sequences, but the low variation in G+U or G+A content, is due to differences in the effects of variation along these axes on the error value. Surprisingly, the biological distribution of error values has far lower variance than randomized error values, but error values of actual codon and amino-acid usages are actually greater than would be expected by chance. CONCLUSION: These unexpected findings suggest that selection against translation error has not produced codon or amino-acid usages that minimize the effects of errors, and that even messages with very different nucleotide compositions somehow maintain a relatively constant error value. They raise the question: why do all known organisms use highly error-minimizing genetic codes, but fail to minimize the errors in the mRNA messages they encode?

Animals↗
PubMed2005

Error minimization and coding triplet/binding site associations are independent features of the canonical genetic code.

The canonical genetic code has been reported both to be error minimizing and to show stereochemical associations between coding triplets and binding sites. In order to test whether these two properties are unexpectedly overlapping, we generated 200,000 randomized genetic codes using each of five randomization schemes, with and without randomization of stop codons. Comparison of the code error (difference in polar requirement for single-nucleotide codon interchanges) with the coding triplet concentrations in RNA binding sites for eight amino acids shows that these properties are independent and uncorrelated. Thus, one is not the result of the other, and error minimization and triplet associations probably arose independently during the history of the genetic code. We explicitly show that prior fixation of a stereochemical core is consistent with an effective later minimization of error.

Base Sequence↗
PubMed2005

Size, constant sequences, and optimal selection.

Because the abundance of functional molecules in RNA sequence space has many unexplored aspects, we compared the outcome of 11 independent selections, performed using the same affinity selection protocol and contiguous randomized regions of 16, 22, 26, 50, 70, and 90 nucleotides. All affinity selections targeted the simplest isoleucine aptamer, an asymmetric internal loop. This loop should be abundant in all selections, so that it can be compared across all experiments. In some cases, two primer sets intended to favor selection of different structures have also been compared. The simplest isoleucine aptamer dominates all selections except with the shortest tract, 16 contiguous randomized nucleotides. Here the isoleucine aptamer cannot be accommodated and no other motif can be selected. Our results suggest an optimum length for selection; surprisingly, both the shortest and the longest randomized tracts make it more difficult to recover the motif. Estimated apparent initial abundances suggest that the simplest isoleucine motif was 20- to 40-fold more frequent in selection with 50- or 70-nucleotide randomized regions than with any other length. Considering primer sets, a pre-formed stable stem within fixed flanking sequences had a five-to 10-fold negative effect on apparent motif abundance at all lengths. Differing random tract lengths also determined the probable motif permutation and the most abundant helix lengths. These data support a significant but lesser role for primer sequences in the outcome of selections.

Base Sequence↗
PubMed2005

tRNA creation by hairpin duplication.

Many studies have suggested that the modern cloverleaf structure of tRNA may have arisen through duplication of a primordial hairpin, but the timing of this duplication event has been unclear. Here we measure the level of sequence identity between the two halves of each of a large sample of tRNAs and compare this level to that of chimeric tRNAs constructed either within or between groups defined by phylogeny and/or specificity. We find that actual tRNAs have significantly more matches between the two halves than do random sequences that can form the tRNA structure, but there is no difference in the average level of matching between the two halves of an individual tRNA and the average level of matching between the two halves of the chimeric tRNAs in any of the sets we constructed. These results support the hypothesis that the modern tRNA cloverleaf arose from a single hairpin duplication prior to the divergence of modern tRNA specificities and the three domains of life.

Base Sequence↗
PubMed2005

Occurrence of the aminoacyl-tRNA synthetases in high-molecular weight complexes correlates with the size of substrate amino acids.

One of the distinctive and mysterious features of mammalian aminoacyl-tRNA synthetases (AARSs) is the existence of stable high-molecular weight complexes containing 10 out of 20 AARSs. The composition and structure of these complexes are conserved among multicellular animals. No specific function associated with these structures has been found, and there is no evident rationale for a particular separation of AARSs in "complex-bound" and "free" forms. We have demonstrated a strong association between the occurrence of AARSs in the complexes and the volume of their substrate amino acids. The significance of this association is discussed in terms of the structural organization of translation in the living cell.

Amino Acids↗