A synthetic genetic edge detection program.

Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.

Massively parallel de novo protein design for targeted therapeutics.

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37-43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.

A Computationally Designed Hemagglutinin Stem-Binding Protein Provides In Vivo Protection from Influenza Independent of a Host Immune Response.

Broadly neutralizing antibodies targeting a highly conserved region in the hemagglutinin (HA) stem protect against influenza infection. Here, we investigate the protective efficacy of a protein (HB36.6) computationally designed to bind with high affinity to the same region in the HA stem. We show that intranasal delivery of HB36.6 affords protection in mice lethally challenged with diverse strains of influenza independent of Fc-mediated effector functions or a host antiviral immune response. This designed protein prevents infection when given as a single dose of 6.0 mg/kg up to 48 hours before viral challenge and significantly reduces disease when administered as a daily therapeutic after challenge. A single dose of 10.0 mg/kg HB36.6 administered 1-day post-challenge resulted in substantially better protection than 10 doses of oseltamivir administered twice daily for 5 days. Thus, binding of HB36.6 to the influenza HA stem region alone, independent of a host response, is sufficient to reduce viral infection and replication in vivo. These studies demonstrate the potential of computationally designed binding proteins as a new class of antivirals for influenza.

Rapid Diagnostic Assay for Intact Influenza Virus Using a High Affinity Hemagglutinin Binding Protein.

Influenza is a ubiquitous and recurring infection that results in approximately 500 000 deaths globally each year. Commercially available rapid diagnostic tests are based upon detection of the influenza nucleoprotein, which are limited in that they are unable to differentiate by species and require an additional viral lysis step. Sample preprocessing can be minimized or eliminated by targeting the intact influenza virus, thereby reducing assay complexity and leveraging the large number of hemagglutinin proteins on the surface of each virus. Here, we report the development of a paper-based influenza assay that targets the hemagglutinin protein; the assay employs a combination of antibodies and novel computationally designed, recombinant affinity proteins as the capture and detection agents. This system leverages the customizability of recombinant protein design to target the conserved receptor-binding pocket of the hemagglutinin protein and to match the trimeric nature of hemagglutinin for improved avidity. Using this assay, we demonstrate the first instance of intact influenza virus detection using a combination of antibody and affinity proteins within a porous network. The recombinant head region binder based assays yield superior analytical sensitivity as compared to the antibody based assay, with lower limits of detection of 3.54 × 107 and 1.34 × 107 CEID50/mL for the mixed and all binder stacks, respectively. Not only does this work describe the development of a novel influenza assay, it also demonstrates the power of recombinant affinity proteins for use in rapid diagnostic assays.

Biogenesis of influenza a virus hemagglutinin cross-protective stem epitopes.

Antigenic variation in the globular domain of influenza A virus (IAV) hemagglutinin (HA) precludes effective immunity to this major human pathogen. Although the HA stem is highly conserved between influenza virus strains, HA stem-reactive antibodies (StRAbs) were long considered biologically inert. It is now clear, however, that StRAbs reduce viral replication in animal models and protect against pathogenicity and death, supporting the potential of HA stem-based immunogens as drift-resistant vaccines. Optimally designing StRAb-inducing immunogens and understanding StRAb effector functions require thorough comprehension of HA stem structure and antigenicity. Here, we study the biogenesis of HA stem epitopes recognized in cells infected with various drifted IAV H1N1 strains using mouse and human StRAbs. Using a novel immunofluorescence (IF)-based assay, we find that human StRAbs bind monomeric HA in the endoplasmic reticulum (ER) and trimerized HA in the Golgi complex (GC) with similar high avidity, potentially good news for producing effective monomeric HA stem immunogens. Though HA stem epitopes are nestled among several N-linked oligosaccharides, glycosylation is not required for full antigenicity. Rather, as N-linked glycans increase in size during intracellular transport of HA through the GC, StRAb binding becomes temperature-sensitive, binding poorly to HA at 4°C and well at 37°C. A de novo designed, 65-residue protein binds the mature HA stem independently of temperature, consistent with a lack of N-linked oligosaccharide steric hindrance due to its small size. Likewise, StRAbs bind recombinant HA carrying simple N-linked glycans in a temperature-independent manner. Chemical cross-linking experiments show that N-linked oligosaccharides likely influence StRAb binding by direct local effects rather than by globally modifying the conformational flexibility of HA. Our findings indicate that StRAb binding to HA is precarious, raising the possibility that sufficient immune pressure on the HA stem region could select for viral escape mutants with increased steric hindrance from N-linked glycans.

Immobilizing affinity proteins to nitrocellulose: a toolbox for paper-based assay developers.

To enable enhanced paper-based diagnostics with improved detection capabilities, new methods are needed to immobilize affinity reagents to porous substrates, especially for capture molecules other than IgG. To this end, we have developed and characterized three novel methods for immobilizing protein-based affinity reagents to nitrocellulose membranes. We have demonstrated these methods using recombinant affinity proteins for the influenza surface protein hemagglutinin, leveraging the customizability of these recombinant "flu binders" for the design of features for immobilization. The three approaches shown are: (1) covalent attachment of thiolated affinity protein to an epoxide-functionalized nitrocellulose membrane, (2) attachment of biotinylated affinity protein through a nitrocellulose-binding streptavidin anchor protein, and (3) fusion of affinity protein to a novel nitrocellulose-binding anchor protein for direct coupling and immobilization. We also characterized the use of direct adsorption for the flu binders, as a point of comparison and motivation for these novel methods. Finally, we demonstrated that these novel methods can provide improved performance to an influenza hemagglutinin assay, compared to a traditional antibody-based capture system. Taken together, this work advances the toolkit available for the development of next-generation paper-based diagnostics.

Characterization of highly active mutational signatures in tumors from a large Chinese population.

The majority of mutational signatures have been characterized in tumors from Western countries and the degree to which mutational signatures are similar or different in Eastern populations has not been fully explored. We leveraged a large-scale clinical sequencing cohort of tumors from a Chinese population containing 25 tumor types and found that the highly active mutational signatures were similar to those previously characterized1,2. The aristolochic acid signature SBS22 was observed in four soft tissue sarcomas and the POLE-associated signature SBS10 was observed in a gallbladder carcinoma. In lung adenocarcinoma, the polycyclic aromatic hydrocarbon (PAH) signature SBS4 was significantly higher in males compared to females but not associated with smoking status. The UV-associated signature SBS7 was significantly lower in cutaneous melanomas from the Chinese population compared to a similar American cohort. Overall, these results add to our understanding of the mutational processes that contribute to tumors from the Chinese population.

Synthetic biology: engineering Escherichia coli to see light.

We have designed a bacterial system that is switched between different states by red light. The system consists of a synthetic sensor kinase that allows a lawn of bacteria to function as a biological film, such that the projection of a pattern of light on to the bacteria produces a high-definition (about 100 megapixels per square inch), two-dimensional chemical image. This spatial control of bacterial gene expression could be used to 'print' complex biological materials, for example, and to investigate signalling pathways through precise spatial and temporal control of their phosphorylation steps.

The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures.

Mutational signatures are patterns of somatic alterations in the genome caused by carcinogenic exposures or aberrant cellular processes. To provide a comprehensive workflow for preprocessing, analysis, and visualization of mutational signatures, we created the Mutational Signature Comprehensive Analysis Toolkit (musicatk) package. musicatk enables users to select different schemas for counting mutation types and to easily combine count tables from different schemas. Multiple distinct methods are available to deconvolute signatures and exposures or to predict exposures in individual samples given a pre-existing set of signatures. Additional exploratory features include the ability to compare signatures to the Catalogue Of Somatic Mutations In Cancer (COSMIC) database, embed tumors in two dimensions with uniform manifold approximation and projection, cluster tumors into subgroups based on exposure frequencies, identify differentially active exposures between tumor subgroups, and plot exposure distributions across user-defined annotations such as tumor type. Overall, musicatk will enable users to gain novel insights into the patterns of mutational signatures observed in cancer cohorts. SIGNIFICANCE: The musicatk package empowers researchers to characterize mutational signatures and tumor heterogeneity with a comprehensive set of preprocessing utilities, discovery and prediction tools, and multiple functions for downstream analysis and visualization.

Genomic Evolutionary Patterns of Leiomyosarcoma and Liposarcoma.

PURPOSE: Leiomyosarcoma and liposarcoma are common subtypes of soft tissue sarcoma (STS). Patients with metastatic leiomyosarcoma or dedifferentiated liposarcoma (DDLPS) typically have worse outcomes compared with localized leiomyosarcoma or well-differentiated liposarcoma (WDLPS). A better understanding of genetic changes between primary/metastatic leiomyosarcoma and between WDLPS/DDLPS may provide insight into their genetic evolution. EXPERIMENTAL DESIGN: We interrogated whole-exome sequencing (WES) from "trios" of normal tissue, primary tumor, and metastatic tumor from individual patients with leiomyosarcoma (n = 9), and trios of normal tissue, well-differentiated tumor, and dedifferentiated tumor from individual patients with liposarcoma (n = 19). Specifically, we performed mutational, copy number, and tumor evolution analyses on these cohorts and compared patterns among leiomyosarcoma and liposarcoma trios. RESULTS: Leiomyosarcoma cases harbored shared drivers through a typical parent/child relationship where the metastatic tumor was derived from the primary tumor. In contrast, while all liposarcoma cases shared the characteristic focal chromosome 12 amplicon, most paired liposarcoma cases did not share additional mutations, suggesting a divergent evolutionary pattern from a common precursor. No highly recurrent genomic alterations from WES were identified that could be implicated as driving the progression of disease in either sarcoma subtype. CONCLUSIONS: From a genomic perspective, leiomyosarcoma metastases contain genetic alterations that are also found in primary tumors. WDLPS and DDLPS, however, appear to divergently evolve from a common precursor harboring 12q amplification, rather than as a transformation to a higher-grade tumor. Further efforts to identify specific drivers of these distinct evolutionary patterns may inform future translational and clinical research in STS.

Global analysis of protein folding using massively parallel design, synthesis, and testing.

Proteins fold into unique native structures stabilized by thousands of weak interactions that collectively overcome the entropic cost of folding. Although these forces are "encoded" in the thousands of known protein structures, "decoding" them is challenging because of the complexity of natural proteins that have evolved for function, not stability. We combined computational protein design, next-generation gene synthesis, and a high-throughput protease susceptibility assay to measure folding and stability for more than 15,000 de novo designed miniproteins, 1000 natural proteins, 10,000 point mutants, and 30,000 negative control sequences. This analysis identified more than 2500 stable designed proteins in four basic folds-a number sufficient to enable us to systematically examine how sequence determines folding and stability in uncharted protein space. Iteration between design and experiment increased the design success rate from 6% to 47%, produced stable proteins unlike those found in nature for topologies where design was initially unsuccessful, and revealed subtle contributions to stability as designs became increasingly optimized. Our approach achieves the long-standing goal of a tight feedback cycle between computation and experiment and has the potential to transform computational protein design into a data-driven science.

Landscape of Genomic Alterations in Pituitary Adenomas.

Purpose: Pituitary adenomas are the second most common primary brain tumor, yet their genetic profiles are incompletely understood.Experimental Design: We performed whole-exome sequencing of 42 pituitary macroadenomas and matched normal DNA. These adenomas included hormonally active and inactive tumors, ones with typical or atypical histology, and ones that were primary or recurrent.Results: We identified mutations, insertions/deletions, and copy-number alterations. Nearly one-third of samples (29%) had chromosome arm-level copy-number alterations across large fractions of the genome. Despite such widespread genomic disruption, these tumors had few focal events, which is unusual among highly disrupted cancers. The other 71% of tumors formed a distinct molecular class, with somatic copy number alterations involving less than 6% of the genome. Among the highly disrupted group, 75% were functional adenomas or atypical null-cell adenomas, whereas 87% of the less-disrupted group were nonfunctional adenomas. We confirmed this association between functional subtype and disruption in a validation dataset of 87 pituitary adenomas. Analysis of previously published expression data from an additional 50 adenomas showed that arm-level alterations significantly impacted transcript levels, and that the disrupted samples were characterized by expression changes associated with poor outcome in other cancers. Arm-level losses of chromosomes 1, 2, 11, and 18 were significantly recurrent. No significantly recurrent mutations were identified, suggesting no genes are altered by exonic mutations across large fractions of pituitary macroadenomas.Conclusions: These data indicate that sporadic pituitary adenomas have distinct copy-number profiles that associate with hormonal and histologic subtypes and influence gene expression. Clin Cancer Res; 23(7); 1841-51. ©2016 AACR.

Genomic landscape of high-grade meningiomas.

High-grade meningiomas frequently recur and are associated with high rates of morbidity and mortality. To determine the factors that promote the development and evolution of these tumors, we analyzed the genomes of 134 high-grade meningiomas and compared this information with data from 587 previously published meningiomas. High-grade meningiomas had a higher mutation burden than low-grade meningiomas but did not harbor any statistically significant mutated genes aside from NF2. High-grade meningiomas also possessed significantly elevated rates of chromosomal gains and losses, especially among tumors with monosomy 22. Meningiomas previously treated with adjuvant radiation had significantly more copy number alterations than radiation-induced or radiation-naïve meningiomas. Across serial recurrences, genomic disruption preceded the emergence of nearly all mutations, remained largely uniform across time, and when present in low-grade meningiomas, correlated with subsequent progression to a higher grade. In contrast to the largely stable copy number alterations, mutations were strikingly heterogeneous across tumor recurrences, likely due to extensive geographic heterogeneity in the primary tumor. While high-grade meningiomas harbored significantly fewer overtly targetable alterations than low-grade meningiomas, they contained numerous mutations that are predicted to be neoantigens, suggesting that immunologic targeting may be of therapeutic value.

Erratum: Genomic landscape of high-grade meningiomas.

[This corrects the article DOI: 10.1038/s41525-017-0014-7.].

The genomic landscape and evolution of endometrial carcinoma progression and abdominopelvic metastasis.

Recent studies have detailed the genomic landscape of primary endometrial cancers, but the evolution of these cancers into metastases has not been characterized. We performed whole-exome sequencing of 98 tumor biopsies including complex atypical hyperplasias, primary tumors and paired abdominopelvic metastases to survey the evolutionary landscape of endometrial cancer. We expanded and reanalyzed The Cancer Genome Atlas (TCGA) data, identifying new recurrent alterations in primary tumors, including mutations in the estrogen receptor cofactor gene NRIP1 in 12% of patients. We found that likely driver events were present in both primary and metastatic tissue samples, with notable exceptions such as ARID1A mutations. Phylogenetic analyses indicated that the sampled metastases typically arose from a common ancestral subclone that was not detected in the primary tumor biopsy. These data demonstrate extensive genetic heterogeneity in endometrial cancers and relative homogeneity across metastatic sites.

Long-term Benefit of PD-L1 Blockade in Lung Cancer Associated with JAK3 Activation.

PD-1 immune checkpoint blockade occasionally results in durable clinical responses in advanced metastatic cancers. However, mechanism-based predictors of response to this immunotherapy remain incompletely characterized. We performed comprehensive genomic profiling on a tumor and germline sample from a patient with refractory lung adenocarcinoma who achieved marked long-term clinical benefit from anti-PD-L1 therapy. We discovered activating somatic and germline amino acid variants in JAK3 that promoted PD-L1 induction in lung cancer cells and in the tumor immune microenvironment. These findings suggest that genomic alterations that deregulate cytokine receptor signal transduction could contribute to PD-L1 activation and engagement of the PD-1 immune checkpoint in lung cancer.

Genomic Characterization of Brain Metastases Reveals Branched Evolution and Potential Therapeutic Targets.

UNLABELLED: Brain metastases are associated with a dismal prognosis. Whether brain metastases harbor distinct genetic alterations beyond those observed in primary tumors is unknown. We performed whole-exome sequencing of 86 matched brain metastases, primary tumors, and normal tissue. In all clonally related cancer samples, we observed branched evolution, where all metastatic and primary sites shared a common ancestor yet continued to evolve independently. In 53% of cases, we found potentially clinically informative alterations in the brain metastases not detected in the matched primary-tumor sample. In contrast, spatially and temporally separated brain metastasis sites were genetically homogenous. Distal extracranial and regional lymph node metastases were highly divergent from brain metastases. We detected alterations associated with sensitivity to PI3K/AKT/mTOR, CDK, and HER2/EGFR inhibitors in the brain metastases. Genomic analysis of brain metastases provides an opportunity to identify potentially clinically informative alterations not detected in clinically sampled primary tumors, regional lymph nodes, or extracranial metastases. SIGNIFICANCE: Decisions for individualized therapies in patients with brain metastasis are often made from primary-tumor biopsies. We demonstrate that clinically actionable alterations present in brain metastases are frequently not detected in primary biopsies, suggesting that sequencing of primary biopsies alone may miss a substantial number of opportunities for targeted therapy.

Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing.

We show that comprehensive sequence-function maps obtained by deep sequencing can be used to reprogram interaction specificity and to leapfrog over bottlenecks in affinity maturation by combining many individually small contributions not detectable in conventional approaches. We use this approach to optimize two computationally designed inhibitors against H1N1 influenza hemagglutinin and, in both cases, obtain variants with subnanomolar binding affinity. The most potent of these, a 51-residue protein, is broadly cross-reactive against all influenza group 1 hemagglutinins, including human H2, and neutralizes H1N1 viruses with a potency that rivals that of several human monoclonal antibodies, demonstrating that computational design followed by comprehensive energy landscape mapping can generate proteins with potential therapeutic utility.

A CMOS Electrochemical Impedance Spectroscopy (EIS) Biosensor Array.

In this paper, we present a fully integrated biosensor 10 × 10 array in a standard complementary metal-oxide semiconducor process, which takes advantage of electrochemical impedance spectroscopy (EIS). We also show that this system is able to detect various biological analytes, such as DNA and proteins, in real time and without the need for molecular labels. In each pixel of this array, we implement a biocompatible Au electrode transducer and embedded sensor circuitry which takes advantage of the coherent detector to measure the impedance of the associated electrode-electrolyte interface. This chip is capable of concurrently measuring admittance values as small as 10(-8) Ω(-1) within the array with the detection dynamic range of more than 90 dB in the frequency range of 10 Hz-50 MHz.