Inducible mismatch repair streamlines forward genetic approaches to target identification of cytotoxic small molecules.

Orphan cytotoxins are small molecules for which the mechanism of action (MoA) is either unknown or ambiguous. Unveiling the mechanism of these compounds may lead to useful tools for biological investigation and new therapeutic leads. In selected cases, the DNA mismatch repair-deficient colorectal cancer cell line, HCT116, has been used as a tool in forward genetic screens to identify compound-resistant mutations, which have ultimately led to target identification. To expand the utility of this approach, we engineered cancer cell lines with inducible mismatch repair deficits, thus providing temporal control over mutagenesis. By screening for compound resistance phenotypes in cells with low or high rates of mutagenesis, we increased both the specificity and sensitivity of identifying resistance mutations. Using this inducible mutagenesis system, we implicate targets for multiple orphan cytotoxins, including a natural product and compounds emerging from a high-throughput screen, thus providing a robust tool for future MoA studies.

HEx: A heterologous expression platform for the discovery of fungal natural products.

For decades, fungi have been a source of U.S. Food and Drug Administration-approved natural products such as penicillin, cyclosporine, and the statins. Recent breakthroughs in DNA sequencing suggest that millions of fungal species exist on Earth, with each genome encoding pathways capable of generating as many as dozens of natural products. However, the majority of encoded molecules are difficult or impossible to access because the organisms are uncultivable or the genes are transcriptionally silent. To overcome this bottleneck in natural product discovery, we developed the HEx (Heterologous EXpression) synthetic biology platform for rapid, scalable expression of fungal biosynthetic genes and their encoded metabolites in Saccharomyces cerevisiae. We applied this platform to 41 fungal biosynthetic gene clusters from diverse fungal species from around the world, 22 of which produced detectable compounds. These included novel compounds with unexpected biosynthetic origins, particularly from poorly studied species. This result establishes the HEx platform for rapid discovery of natural products from any fungal species, even those that are uncultivable, and opens the door to discovery of the next generation of natural products.

Influence of Radiographic Positioning on Canine Sacroiliac and Lumbosacral Angle Measurements.

OBJECTIVES: To evaluate the influence of radiographic malpositioning on canine sacroiliac and lumbosacral inclination angles. METHODS: Using canine cadavers, lateral pelvic radiographs were acquired with the radiographic beam in a neutral position and then rotated 5, 10 and 15° to mimic rotational malpositioning. The focal point of the beam was then focused over the abdomen and again over mid-diaphysis of the femur to mimic an abdominal or femoral radiographic study. RESULTS: Five degrees of rotational malpositioning did not influence measurements of sacroiliac or lumbosacral inclination, but malpositioning by more than 5° led to a significant decrease in both sacroiliac and lumbosacral angles. Moving the focal point to the femur significantly decreased the measured lumbosacral angle. Abdominally centred radiographs had no effect on lumbosacral and sacroiliac angle measurements. CLINICAL SIGNIFICANCE: When evaluating canine lumbosacral and sacroiliac angles radiographically, pelvic rotation of more than 5° should be avoided as should the use of lateral radiographs centred over the femur.

Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases.

Genetic studies of human disease have traditionally focused on the detection of disease-causing mutations in afflicted individuals. Here we describe a complementary approach that seeks to identify healthy individuals resilient to highly penetrant forms of genetic childhood disorders. A comprehensive screen of 874 genes in 589,306 genomes led to the identification of 13 adults harboring mutations for 8 severe Mendelian conditions, with no reported clinical manifestation of the indicated disease. Our findings demonstrate the promise of broadening genetic studies to systematically search for well individuals who are buffering the effects of rare, highly penetrant, deleterious mutations. They also indicate that incomplete penetrance for Mendelian diseases is likely more common than previously believed. The identification of resilient individuals may provide a first step toward uncovering protective genetic variants that could help elucidate the mechanisms of Mendelian diseases and new therapeutic strategies.

Multi-cellular 3D human primary liver cell culture elevates metabolic activity under fluidic flow.

We have developed a low-cost liver cell culture device that creates fluidic flow over a 3D primary liver cell culture that consists of multiple liver cell types, including hepatocytes and non-parenchymal cells (fibroblasts, stellate cells, and Kupffer cells). We tested the performance of the cell culture under fluidic flow for 14 days, finding that hepatocytes produced albumin and urea at elevated levels compared to static cultures. Hepatocytes also responded with induction of P450 (CYP1A1 and CYP3A4) enzyme activity when challenged with P450 inducers, although we did not find significant differences between static and fluidic cultures. Non-parenchymal cells were similarly responsive, producing interleukin 8 (IL-8) when challenged with 10 µM bacterial lipoprotein (LPS). To create the fluidic flow in an inexpensive manner, we used a rocking platform that tilts the cell culture devices at angles between ±12°, resulting in a periodically changing hydrostatic pressure drop between reservoirs and the accompanying periodically changing fluidic flow (average flow rate of 650 µL min(-1), and a maximum shear stress of 0.64 dyne cm(-2)). The increase in metabolic activity is consistent with the hypothesis that, similar to unidirectional fluidic flow, primary liver cell cultures increase their metabolic activity in response to fluidic flow periodically changes direction. Since fluidic flow that changes direction periodically drastically changes the behavior of other cells types that are shear sensitive, our findings support the theory that the increase in hepatic metabolic activity associated with fluidic flow is either activated by mechanisms other than shear sensing (for example increased opportunities for gas and metabolite exchange), or that it follows a shear sensing mechanism that does not depend on the direction of shear. Our mode of device operation allows us to evaluate drugs under fluidic cell culture conditions and at low device manufacturing and operation costs.

A long-term three dimensional liver co-culture system for improved prediction of clinically relevant drug-induced hepatotoxicity.

Drug-induced liver injury (DILI) is the major cause for liver failure and post-marketing drug withdrawals. Due to species-specific differences in hepatocellular function, animal experiments to assess potential liabilities of drug candidates can predict hepatotoxicity in humans only to a certain extent. In addition to animal experimentation, primary hepatocytes from rat or human are widely used for pre-clinical safety assessment. However, as many toxic responses in vivo are mediated by a complex interplay among different cell types and often require chronic drug exposures, the predictive performance of hepatocytes is very limited. Here, we established and characterized human and rat in vitro three-dimensional (3D) liver co-culture systems containing primary parenchymal and non-parenchymal hepatic cells. Our data demonstrate that cells cultured on a 3D scaffold have a preserved composition of hepatocytes, stellate, Kupffer and endothelial cells and maintain liver function for up to 3months, as measured by the production of albumin, fibrinogen, transferrin and urea. Additionally, 3D liver co-cultures maintain cytochrome P450 inducibility, form bile canaliculi-like structures and respond to inflammatory stimuli. Upon incubation with selected hepatotoxicants including drugs which have been shown to induce idiosyncratic toxicity, we demonstrated that this model better detected in vivo drug-induced toxicity, including species-specific drug effects, when compared to monolayer hepatocyte cultures. In conclusion, our results underline the importance of more complex and long lasting in vitro cell culture models that contain all liver cell types and allow repeated drug-treatments for detection of in vivo-relevant adverse drug effects.

Efficient replication of over 180 genetic associations with self-reported medical data.

While the cost and speed of generating genomic data have come down dramatically in recent years, the slow pace of collecting medical data for large cohorts continues to hamper genetic research. Here we evaluate a novel online framework for obtaining large amounts of medical information from a recontactable cohort by assessing our ability to replicate genetic associations using these data. Using web-based questionnaires, we gathered self-reported data on 50 medical phenotypes from a generally unselected cohort of over 20,000 genotyped individuals. Of a list of genetic associations curated by NHGRI, we successfully replicated about 75% of the associations that we expected to (based on the number of cases in our cohort and reported odds ratios, and excluding a set of associations with contradictory published evidence). Altogether we replicated over 180 previously reported associations, including many for type 2 diabetes, prostate cancer, cholesterol levels, and multiple sclerosis. We found significant variation across categories of conditions in the percentage of expected associations that we were able to replicate, which may reflect systematic inflation of the effects in some initial reports, or differences across diseases in the likelihood of misdiagnosis or misreport. We also demonstrated that we could improve replication success by taking advantage of our recontactable cohort, offering more in-depth questions to refine self-reported diagnoses. Our data suggest that online collection of self-reported data from a recontactable cohort may be a viable method for both broad and deep phenotyping in large populations.

Web-based, participant-driven studies yield novel genetic associations for common traits.

Despite the recent rapid growth in genome-wide data, much of human variation remains entirely unexplained. A significant challenge in the pursuit of the genetic basis for variation in common human traits is the efficient, coordinated collection of genotype and phenotype data. We have developed a novel research framework that facilitates the parallel study of a wide assortment of traits within a single cohort. The approach takes advantage of the interactivity of the Web both to gather data and to present genetic information to research participants, while taking care to correct for the population structure inherent to this study design. Here we report initial results from a participant-driven study of 22 traits. Replications of associations (in the genes OCA2, HERC2, SLC45A2, SLC24A4, IRF4, TYR, TYRP1, ASIP, and MC1R) for hair color, eye color, and freckling validate the Web-based, self-reporting paradigm. The identification of novel associations for hair morphology (rs17646946, near TCHH; rs7349332, near WNT10A; and rs1556547, near OFCC1), freckling (rs2153271, in BNC2), the ability to smell the methanethiol produced after eating asparagus (rs4481887, near OR2M7), and photic sneeze reflex (rs10427255, near ZEB2, and rs11856995, near NR2F2) illustrates the power of the approach.

A graph-based motif detection algorithm models complex nucleotide dependencies in transcription factor binding sites.

Given a set of known binding sites for a specific transcription factor, it is possible to build a model of the transcription factor binding site, usually called a motif model, and use this model to search for other sites that bind the same transcription factor. Typically, this search is performed using a position-specific scoring matrix (PSSM), also known as a position weight matrix. In this paper we analyze a set of eukaryotic transcription factor binding sites and show that there is extensive clustering of similar k-mers in eukaryotic motifs, owing to both functional and evolutionary constraints. The apparent limitations of probabilistic models in representing complex nucleotide dependencies lead us to a graph-based representation of motifs. When deciding whether a candidate k-mer is part of a motif or not, we base our decision not on how well the k-mer conforms to a model of the motif as a whole, but how similar it is to specific, known k-mers in the motif. We elucidate the reasons why we expect graph-based methods to perform well on motif data. Our MotifScan algorithm shows greatly improved performance over the prevalent PSSM-based method for the detection of eukaryotic motifs.

MotifCut: regulatory motifs finding with maximum density subgraphs.

MOTIVATION: DNA motif finding is one of the core problems in computational biology, for which several probabilistic and discrete approaches have been developed. Most existing methods formulate motif finding as an intractable optimization problem and rely either on expectation maximization (EM) or on local heuristic searches. Another challenge is the choice of motif model: simpler models such as the position-specific scoring matrix (PSSM) impose biologically unrealistic assumptions such as independence of the motif positions, while more involved models are harder to parametrize and learn. RESULTS: We present MotifCut, a graph-theoretic approach to motif finding leading to a convex optimization problem with a polynomial time solution. We build a graph where the vertices represent all k-mers in the input sequences, and edges represent pairwise k-mer similarity. In this graph, we search for a motif as the maximum density subgraph, which is a set of k-mers that exhibit a large number of pairwise similarities. Our formulation does not make strong assumptions regarding the structure of the motif and in practice both motifs that fit well the PSSM model, and those that exhibit strong dependencies between position pairs are found as dense subgraphs. We benchmark MotifCut on both synthetic and real yeast motifs, and find that it compares favorably to existing popular methods. The ability of MotifCut to detect motifs appears to scale well with increasing input size. Moreover, the motifs we discover are different from those discovered by the other methods. AVAILABILITY: MotifCut server and other materials can be found at motifcut.stanford.edu.