Direct Molecular Evidence for an Ancient, Conserved Developmental Toolkit Controlling Posttranscriptional Gene Regulation in Land Plants.

In plants, miRNA production is orchestrated by a suite of proteins that control transcription of the pri-miRNA gene, post-transcriptional processing and nuclear export of the mature miRNA. Post-transcriptional processing of miRNAs is controlled by a pair of physically interacting proteins, hyponastic leaves 1 (HYL1) and Dicer-like 1 (DCL1). However, the evolutionary history and structural basis of the HYL1-DCL1 interaction is unknown. Here we use ancestral sequence reconstruction and functional characterization of ancestral HYL1 in vitro and in Arabidopsis thaliana to better understand the origin and evolution of the HYL1-DCL1 interaction and its impact on miRNA production and plant development. We found the ancestral plant HYL1 evolved high affinity for both double-stranded RNA (dsRNA) and its DCL1 partner before the divergence of mosses from seed plants (∼500 Ma), and these high-affinity interactions remained largely conserved throughout plant evolutionary history. Structural modeling and molecular binding experiments suggest that the second of two dsRNA-binding motifs (DSRMs) in HYL1 may interact tightly with the first of two C-terminal DCL1 DSRMs to mediate the HYL1-DCL1 physical interaction necessary for efficient miRNA production. Transgenic expression of the nearly 200 Ma-old ancestral flowering-plant HYL1 in A. thaliana was sufficient to rescue many key aspects of plant development disrupted by HYL1- knockout and restored near-native miRNA production, suggesting that the functional partnership of HYL1-DCL1 originated very early in and was strongly conserved throughout the evolutionary history of terrestrial plants. Overall, our results are consistent with a model in which miRNA-based gene regulation evolved as part of a conserved plant "developmental toolkit."

eCOMPASS: evaluative comparison of multiple protein alignments by statistical score.

MOTIVATION: Detecting subtle biologically relevant patterns in protein sequences often requires the construction of a large and accurate multiple sequence alignment (MSA). Methods for constructing MSAs are usually evaluated using benchmark alignments, which, however, typically contain very few sequences and are therefore inappropriate when dealing with large numbers of proteins. RESULTS: eCOMPASS addresses this problem using a statistical measure of relative alignment quality based on direct coupling analysis (DCA): to maintain protein structural integrity over evolutionary time, substitutions at one residue position typically result in compensating substitutions at other positions. eCOMPASS computes the statistical significance of the congruence between high scoring directly coupled pairs and 3D contacts in corresponding structures, which depends upon properly aligned homologous residues. We illustrate eCOMPASS using both simulated and real MSAs. AVAILABILITY AND IMPLEMENTATION: The eCOMPASS executable, C++ open source code and input data sets are available at https://www.igs.umaryland.edu/labs/neuwald/software/compass. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dicer cleaves 5'-extended microRNA precursors originating from RNA polymerase II transcription start sites.

MicroRNAs (miRNAs) are approximately 22 nucleotide (nt) long and play important roles in post-transcriptional regulation in both plants and animals. In animals, precursor (pre-) miRNAs are ∼70 nt hairpins produced by Drosha cleavage of long primary (pri-) miRNAs in the nucleus. Exportin-5 (XPO5) transports pre-miRNAs into the cytoplasm for Dicer processing. Alternatively, pre-miRNAs containing a 5' 7-methylguanine (m7G-) cap can be generated independently of Drosha and XPO5. Here we identify a class of m7G-capped pre-miRNAs with 5' extensions up to 39 nt long. The 5'-extended pre-miRNAs are transported by Exportin-1 (XPO1). Unexpectedly, a long 5' extension does not block Dicer processing. Rather, Dicer directly cleaves 5'-extended pre-miRNAs by recognizing its 3' end to produce mature 3p miRNA and extended 5p miRNA both in vivo and in vitro. The recognition of 5'-extended pre-miRNAs by the Dicer Platform-PAZ-Connector (PPC) domain can be traced back to ancestral animal Dicers, suggesting that this previously unrecognized Dicer reaction mode is evolutionarily conserved. Our work reveals additional genetic sources for small regulatory RNAs and substantiates Dicer's essential role in RNAi-based gene regulation.

Increased Affinity for RNA Targets Evolved Early in Animal and Plant Dicer Lineages through Different Structural Mechanisms.

Understanding the structural basis for evolutionary changes in protein function is central to molecular evolutionary biology and can help determine the extent to which functional convergence occurs through similar or different structural mechanisms. Here, we combine ancestral sequence reconstruction with functional characterization and structural modeling to directly examine the evolution of sequence-structure-function across the early differentiation of animal and plant Dicer/DCL proteins, which perform the first molecular step in RNA interference by identifying target RNAs and processing them into short interfering products. We found that ancestral Dicer/DCL proteins evolved similar increases in RNA target affinities as they diverged independently in animal and plant lineages. In both cases, increases in RNA target affinities were associated with sequence changes that anchored the RNA's 5'phosphate, but the structural bases for 5'phosphate recognition were different in animal versus plant lineages. These results highlight how molecular-functional evolutionary convergence can derive from the evolution of unique protein structures implementing similar biochemical mechanisms.

Convergence of Domain Architecture, Structure, and Ligand Affinity in Animal and Plant RNA-Binding Proteins.

Reconstruction of ancestral protein sequences using phylogenetic methods is a powerful technique for directly examining the evolution of molecular function. Although ancestral sequence reconstruction (ASR) is itself very efficient, downstream functional, and structural studies necessary to characterize when and how changes in molecular function occurred are often costly and time-consuming, currently limiting ASR studies to examining a relatively small number of discrete functional shifts. As a result, we have very little direct information about how molecular function evolves across large protein families. Here we develop an approach combining ASR with structure and function prediction to efficiently examine the evolution of ligand affinity across a large family of double-stranded RNA binding proteins (DRBs) spanning animals and plants. We find that the characteristic domain architecture of DRBs-consisting of 2-3 tandem double-stranded RNA binding motifs (dsrms)-arose independently in early animal and plant lineages. The affinity with which individual dsrms bind double-stranded RNA appears to have increased and decreased often across both animal and plant phylogenies, primarily through convergent structural mechanisms involving RNA-contact residues within the ß1-ß2 loop and a small region of α2. These studies provide some of the first direct information about how protein function evolves across large gene families and suggest that changes in molecular function may occur often and unassociated with major phylogenetic events, such as gene or domain duplications.

Improving the accuracy of high-throughput protein-protein affinity prediction may require better training data.

BACKGROUND: One goal of structural biology is to understand how a protein's 3-dimensional conformation determines its capacity to interact with potential ligands. In the case of small chemical ligands, deconstructing a static protein-ligand complex into its constituent atom-atom interactions is typically sufficient to rapidly predict ligand affinity with high accuracy (>70% correlation between predicted and experimentally-determined affinity), a fact that is exploited to support structure-based drug design. We recently found that protein-DNA/RNA affinity can also be predicted with high accuracy using extensions of existing techniques, but protein-protein affinity could not be predicted with >60% correlation, even when the protein-protein complex was available. METHODS: X-ray and NMR structures of protein-protein complexes, their associated binding affinities and experimental conditions were obtained from different binding affinity and structural databases. Statistical models were implemented using a generalized linear model framework, including the experimental conditions as new model features. We evaluated the potential for new features to improve affinity prediction models by calculating the Pearson correlation between predicted and experimental binding affinities on the training and test data after model fitting and after cross-validation. Differences in accuracy were assessed using two-sample t test and nonparametric Mann-Whitney U test. RESULTS: Here we evaluate a range of potential factors that may interfere with accurate protein-protein affinity prediction. We find that X-ray crystal resolution has the strongest single effect on protein-protein affinity prediction. Limiting our analyses to only high-resolution complexes (≤2.5 Å) increased the correlation between predicted and experimental affinity from 54 to 68% (p = 4.32x10-3). In addition, incorporating information on the experimental conditions under which affinities were measured (pH, temperature and binding assay) had significant effects on prediction accuracy. We also highlight a number of potential errors in large structure-affinity databases, which could affect both model training and accuracy assessment. CONCLUSIONS: The results suggest that the accuracy of statistical models for protein-protein affinity prediction may be limited by the information present in databases used to train new models. Improving our capacity to integrate large-scale structural and functional information may be required to substantively advance our understanding of the general principles by which a protein's structure determines its function.

Resurrecting ancestral structural dynamics of an antiviral immune receptor: adaptive binding pocket reorganization repeatedly shifts RNA preference.

BACKGROUND: Although resurrecting ancestral proteins is a powerful tool for understanding the molecular-functional evolution of gene families, nearly all studies have examined proteins functioning in relatively stable biological processes. The extent to which more dynamic systems obey the same 'rules' governing stable processes is unclear. Here we present the first detailed investigation of the functional evolution of the RIG-like receptors (RLRs), a family of innate immune receptors that detect viral RNA in the cytoplasm. RESULTS: Using kinetic binding assays and molecular dynamics simulations of ancestral proteins, we demonstrate how a small number of adaptive protein-coding changes repeatedly shifted the RNA preference of RLRs throughout animal evolution by reorganizing the shape and electrostatic distribution across the RNA binding pocket, altering the hydrogen bond network between the RLR and its RNA target. In contrast to observations of proteins involved in metabolism and development, we find that RLR-RNA preference 'flip flopped' between two functional states, and shifts in RNA preference were not always coupled to gene duplications or speciation events. We demonstrate at least one reversion of RLR-RNA preference from a derived to an ancestral function through a novel structural mechanism, indicating multiple structural implementations of similar functions. CONCLUSIONS: Our results suggest a model in which frequent shifts in selection pressures imposed by an evolutionary arms race preclude the long-term functional optimization observed in stable biological systems. As a result, the evolutionary dynamics of immune receptors may be less constrained by structural epistasis and historical contingency.

Ancient origins of vertebrate-specific innate antiviral immunity.

Animals deploy various molecular sensors to detect pathogen infections. RIG-like receptor (RLR) proteins identify viral RNAs and initiate innate immune responses. The three human RLRs recognize different types of RNA molecules and protect against different viral pathogens. The RLR protein family is widely thought to have originated shortly before the emergence of vertebrates and rapidly diversified through a complex process of domain grafting. Contrary to these findings, here we show that full-length RLRs and their downstream signaling molecules were present in the earliest animals, suggesting that the RLR-based immune system arose with the emergence of multicellularity. Functional differentiation of RLRs occurred early in animal evolution via simple gene duplication followed by modifications of the RNA-binding pocket, many of which may have been adaptively driven. Functional analysis of human and ancestral RLRs revealed that the ancestral RLR displayed RIG-1-like RNA-binding. MDA5-like binding arose through changes in the RNA-binding pocket following the duplication of the ancestral RLR, which may have occurred either early in Bilateria or later, after deuterostomes split from protostomes. The sensitivity and specificity with which RLRs bind different RNA structures has repeatedly adapted throughout mammalian evolution, suggesting a long-term evolutionary arms race with viral RNA or other molecules.

Evolution of animal and plant dicers: early parallel duplications and recurrent adaptation of antiviral RNA binding in plants.

RNA interference (RNAi) is a eukaryotic molecular system that serves two primary functions: 1) gene regulation and 2) protection against selfish elements such as viruses and transposable DNA. Although the biochemistry of RNAi has been detailed in model organisms, very little is known about the broad-scale patterns and forces that have shaped RNAi evolution. Here, we provide a comprehensive evolutionary analysis of the Dicer protein family, which carries out the initial RNA recognition and processing steps in the RNAi pathway. We show that Dicer genes duplicated and diversified independently in early animal and plant evolution, coincident with the origins of multicellularity. We identify a strong signature of long-term protein-coding adaptation that has continually reshaped the RNA-binding pocket of the plant Dicer responsible for antiviral immunity, suggesting an evolutionary arms race with viral factors. We also identify key changes in Dicer domain architecture and sequence leading to specialization in either gene-regulatory or protective functions in animal and plant paralogs. As a whole, these results reveal a dynamic picture in which the evolution of Dicer function has driven elaboration of parallel RNAi functional pathways in animals and plants.

Adaptive expansion of the maize maternally expressed gene (Meg) family involves changes in expression patterns and protein secondary structures of its members.

BACKGROUND: The Maternally expressed gene (Meg) family is a locally-duplicated gene family of maize which encodes cysteine-rich proteins (CRPs). The founding member of the family, Meg1, is required for normal development of the basal endosperm transfer cell layer (BETL) and is involved in the allocation of maternal nutrients to growing seeds. Despite the important roles of Meg1 in maize seed development, the evolutionary history of the Meg cluster and the activities of the duplicate genes are not understood. RESULTS: In maize, the Meg gene cluster resides in a 2.3 Mb-long genomic region that exhibits many features of non-centromeric heterochromatin. Using phylogenetic reconstruction and syntenic alignments, we identified the pedigree of the Meg family, in which 11 of its 13 members arose in maize after allotetraploidization ~4.8 mya. Phylogenetic and population-genetic analyses identified possible signatures suggesting recent positive selection in Meg homologs. Structural analyses of the Meg proteins indicated potentially adaptive changes in secondary structure from α-helix to ß-strand during the expansion. Transcriptomic analysis of the maize endosperm indicated that 6 Meg genes are selectively activated in the BETL, and younger Meg genes are more active than older ones. In endosperms from B73 by Mo17 reciprocal crosses, most Meg genes did not display parent-specific expression patterns. CONCLUSIONS: Recently-duplicated Meg genes have different protein secondary structures, and their expressions in the BETL dominate over those of older members. Together with the signs of positive selections in the young Meg genes, these results suggest that the expansion of the Meg family involves potentially adaptive transitions in which new members with novel functions prevailed over older members.

Ancestral protein reconstruction reveals evolutionary events governing variation in Dicer helicase function.

Antiviral defense in ecdysozoan invertebrates requires Dicer with a helicase domain capable of ATP hydrolysis. But despite well-conserved ATPase motifs, human Dicer is incapable of ATP hydrolysis, consistent with a muted role in antiviral defense. To investigate this enigma, we used ancestral protein reconstruction to resurrect Dicer's helicase in animals and trace the evolutionary trajectory of ATP hydrolysis. Biochemical assays indicated ancient Dicer possessed ATPase function, that like extant invertebrate Dicers, is stimulated by dsRNA. Analyses revealed that dsRNA stimulates ATPase activity by increasing ATP affinity, reflected in Michaelis constants. Deuterostome Dicer-1 ancestor, while exhibiting lower dsRNA affinity, retained some ATPase activity; importantly, ATPase activity was undetectable in the vertebrate Dicer-1 ancestor, which had even lower dsRNA affinity. Reverting residues in the ATP hydrolysis pocket was insufficient to rescue hydrolysis, but additional substitutions distant from the pocket rescued vertebrate Dicer-1's ATPase function. Our work suggests Dicer lost ATPase function in the vertebrate ancestor due to loss of ATP affinity, involving motifs distant from the active site, important for coupling dsRNA binding to the active conformation. By competing with Dicer for viral dsRNA, RIG-I-like receptors important for interferon signaling may have allowed or actively caused loss of ATPase function.

Recurrent adaptation in RNA interference genes across the Drosophila phylogeny.

RNA interference (RNAi) is quickly emerging as a vital component of genome organization, gene regulation, and immunity in Drosophila and other species. Previous studies have suggested that, as a whole, genes involved in RNAi are under intense positive selection in Drosophila melanogaster. Here, we characterize the extent and patterns of adaptive evolution in 23 known Drosophila RNAi genes, both within D. melanogaster and across the Drosophila phylogeny. We find strong evidence for recurrent protein-coding adaptation at a large number of RNAi genes, particularly those involved in antiviral immunity and defense against transposable elements. We identify specific functional domains involved in direct protein-RNA interactions as particular hotspots of recurrent adaptation in multiple RNAi genes, suggesting that targeted coadaptive arms races may be a general feature of RNAi evolution. Our observations suggest a predictive model of how selective pressures generated by evolutionary arms race scenarios may affect multiple genes across protein interaction networks and other biochemical pathways.

Reconstruction of Nitrogenase Predecessors Suggests Origin from Maturase-Like Proteins.

The evolution of biological nitrogen fixation, uniquely catalyzed by nitrogenase enzymes, has been one of the most consequential biogeochemical innovations over life's history. Though understanding the early evolution of nitrogen fixation has been a longstanding goal from molecular, biogeochemical, and planetary perspectives, its origins remain enigmatic. In this study, we reconstructed the evolutionary histories of nitrogenases, as well as homologous maturase proteins that participate in the assembly of the nitrogenase active-site cofactor but are not able to fix nitrogen. We combined phylogenetic and ancestral sequence inference with an analysis of predicted functionally divergent sites between nitrogenases and maturases to infer the nitrogen-fixing capabilities of their shared ancestors. Our results provide phylogenetic constraints to the emergence of nitrogen fixation and are consistent with a model wherein nitrogenases emerged from maturase-like predecessors. Though the precise functional role of such a predecessor protein remains speculative, our results highlight evolutionary contingency as a significant factor shaping the evolution of a biogeochemically essential enzyme.

Open label safety and efficacy pilot to study mitigation of equine recurrent uveitis through topical suppressor of cytokine signaling-1 mimetic peptide.

Equine recurrent uveitis (ERU) is a painful and debilitating autoimmune disease and represents the only spontaneous model of human recurrent uveitis (RU). Despite the efficacy of existing treatments, RU remains a leading cause of visual handicap in horses and humans. Cytokines, which utilize Janus kinase 2 (Jak2) for signaling, drive the inflammatory processes in ERU that promote blindness. Notably, suppressor of cytokine signaling 1 (SOCS1), which naturally limits the activation of Jak2 through binding interactions, is often deficient in autoimmune disease patients. Significantly, we previously showed that topical administration of a SOCS1 peptide mimic (SOCS1-KIR) mitigated induced rodent uveitis. In this pilot study, we test the potential to translate the therapeutic efficacy observed in experimental rodent uveitis to equine patient disease. Through bioinformatics and peptide binding assays we demonstrate putative binding of the SOCS1-KIR peptide to equine Jak2. We also show that topical, or intravitreal injection of SOCS1-KIR was well tolerated within the equine eye through physical and ophthalmic examinations. Finally, we show that topical SOCS1-KIR administration was associated with significant clinical ERU improvement. Together, these results provide a scientific rationale, and supporting experimental evidence for the therapeutic use of a SOCS1 mimetic peptide in RU.

Robustness of ancestral sequence reconstruction to phylogenetic uncertainty.

Ancestral sequence reconstruction (ASR) is widely used to formulate and test hypotheses about the sequences, functions, and structures of ancient genes. Ancestral sequences are usually inferred from an alignment of extant sequences using a maximum likelihood (ML) phylogenetic algorithm, which calculates the most likely ancestral sequence assuming a probabilistic model of sequence evolution and a specific phylogeny--typically the tree with the ML. The true phylogeny is seldom known with certainty, however. ML methods ignore this uncertainty, whereas Bayesian methods incorporate it by integrating the likelihood of each ancestral state over a distribution of possible trees. It is not known whether Bayesian approaches to phylogenetic uncertainty improve the accuracy of inferred ancestral sequences. Here, we use simulation-based experiments under both simplified and empirically derived conditions to compare the accuracy of ASR carried out using ML and Bayesian approaches. We show that incorporating phylogenetic uncertainty by integrating over topologies very rarely changes the inferred ancestral state and does not improve the accuracy of the reconstructed ancestral sequence. Ancestral state reconstructions are robust to uncertainty about the underlying tree because the conditions that produce phylogenetic uncertainty also make the ancestral state identical across plausible trees; conversely, the conditions under which different phylogenies yield different inferred ancestral states produce little or no ambiguity about the true phylogeny. Our results suggest that ML can produce accurate ASRs, even in the face of phylogenetic uncertainty. Using Bayesian integration to incorporate this uncertainty is neither necessary nor beneficial.

INTREPID: a web server for prediction of functionally important residues by evolutionary analysis.

We present the INTREPID web server for predicting functionally important residues in proteins. INTREPID has been shown to boost the recall and precision of catalytic residue prediction over other sequence-based methods and can be used to identify other types of functional residues. The web server takes an input protein sequence, gathers homologs, constructs a multiple sequence alignment and phylogenetic tree and finally runs the INTREPID method to assign a score to each position. Residues predicted to be functionally important are displayed on homologous 3D structures (where available), highlighting spatial patterns of conservation at various significance thresholds. The INTREPID web server is available at http://phylogenomics.berkeley.edu/intrepid.

Performance of maximum parsimony and likelihood phylogenetics when evolution is heterogeneous.

All inferences in comparative biology depend on accurate estimates of evolutionary relationships. Recent phylogenetic analyses have turned away from maximum parsimony towards the probabilistic techniques of maximum likelihood and bayesian Markov chain Monte Carlo (BMCMC). These probabilistic techniques represent a parametric approach to statistical phylogenetics, because their criterion for evaluating a topology--the probability of the data, given the tree--is calculated with reference to an explicit evolutionary model from which the data are assumed to be identically distributed. Maximum parsimony can be considered nonparametric, because trees are evaluated on the basis of a general metric--the minimum number of character state changes required to generate the data on a given tree--without assuming a specific distribution. The shift to parametric methods was spurred, in large part, by studies showing that although both approaches perform well most of the time, maximum parsimony is strongly biased towards recovering an incorrect tree under certain combinations of branch lengths, whereas maximum likelihood is not. All these evaluations simulated sequences by a largely homogeneous evolutionary process in which data are identically distributed. There is ample evidence, however, that real-world gene sequences evolve heterogeneously and are not identically distributed. Here we show that maximum likelihood and BMCMC can become strongly biased and statistically inconsistent when the rates at which sequence sites evolve change non-identically over time. Maximum parsimony performs substantially better than current parametric methods over a wide range of conditions tested, including moderate heterogeneity and phylogenetic problems not normally considered difficult.

Alignment-Integrated Reconstruction of Ancestral Sequences Improves Accuracy.

Ancestral sequence reconstruction (ASR) uses an alignment of extant protein sequences, a phylogeny describing the history of the protein family and a model of the molecular-evolutionary process to infer the sequences of ancient proteins, allowing researchers to directly investigate the impact of sequence evolution on protein structure and function. Like all statistical inferences, ASR can be sensitive to violations of its underlying assumptions. Previous studies have shown that, whereas phylogenetic uncertainty has only a very weak impact on ASR accuracy, uncertainty in the protein sequence alignment can more strongly affect inferred ancestral sequences. Here, we show that errors in sequence alignment can produce errors in ASR across a range of realistic and simplified evolutionary scenarios. Importantly, sequence reconstruction errors can lead to errors in estimates of structural and functional properties of ancestral proteins, potentially undermining the reliability of analyses relying on ASR. We introduce an alignment-integrated ASR approach that combines information from many different sequence alignments. We show that integrating alignment uncertainty improves ASR accuracy and the accuracy of downstream structural and functional inferences, often performing as well as highly accurate structure-guided alignment. Given the growing evidence that sequence alignment errors can impact the reliability of ASR studies, we recommend that future studies incorporate approaches to mitigate the impact of alignment uncertainty. Probabilistic modeling of insertion and deletion events has the potential to radically improve ASR accuracy when the model reflects the true underlying evolutionary history, but further studies are required to thoroughly evaluate the reliability of these approaches under realistic conditions.

Reconstructing the evolutionary history of nitrogenases: Evidence for ancestral molybdenum-cofactor utilization.

The nitrogenase metalloenzyme family, essential for supplying fixed nitrogen to the biosphere, is one of life's key biogeochemical innovations. The three forms of nitrogenase differ in their metal dependence, each binding either a FeMo-, FeV-, or FeFe-cofactor where the reduction of dinitrogen takes place. The history of nitrogenase metal dependence has been of particular interest due to the possible implication that ancient marine metal availabilities have significantly constrained nitrogenase evolution over geologic time. Here, we reconstructed the evolutionary history of nitrogenases, and combined phylogenetic reconstruction, ancestral sequence inference, and structural homology modeling to evaluate the potential metal dependence of ancient nitrogenases. We find that active-site sequence features can reliably distinguish extant Mo-nitrogenases from V- and Fe-nitrogenases and that inferred ancestral sequences at the deepest nodes of the phylogeny suggest these ancient proteins most resemble modern Mo-nitrogenases. Taxa representing early-branching nitrogenase lineages lack one or more biosynthetic nifE and nifN genes that both contribute to the assembly of the FeMo-cofactor in studied organisms, suggesting that early Mo-nitrogenases may have utilized an alternate and/or simplified pathway for cofactor biosynthesis. Our results underscore the profound impacts that protein-level innovations likely had on shaping global biogeochemical cycles throughout the Precambrian, in contrast to organism-level innovations that characterize the Phanerozoic Eon.

pime: A package for discovery of novel differences among microbial communities.

The data used for profiling microbial communities is usually sparse with some microbes having high abundance in a few samples and being nearly absent in others. However, current bioinformatics tools able to deal with this sparsity are lacking. pime (Prevalence Interval for Microbiome Evaluation) was designed to remove those taxa that may be high in relative abundance in just a few samples but have a low prevalence overall. The reliability and robustness of pime were compared against existing methods and tested using 16S rRNA independent data sets. pime filters microbial taxa not shared in a per treatment prevalence interval started at 5% prevalence with increasing increments of 5% at each filtering step. For each prevalence interval, hundreds of decision trees were calculated to predict the likelihood of detecting differences in treatments. The best prevalence-filtered data set was user-selected by choosing the prevalence interval that kept a large portion of the 16S rRNA sequences in the data set while also showing the lowest error rate. To obtain the likelihood of introducing type I error while building prevalence-filtered data sets, an error detection step based was also included. A pime reanalysis of published data sets uncovered other expected microbial associations than previously reported, which may be masked when only relative abundance was considered.