Shaping the future US bioeconomy through safety, security, sustainability, and social responsibility.

Biomanufacturing practitioners and researchers describe the norms that should govern the growing, global field, to include safety, security, sustainability, and social responsibility. These '4S Principles' should be broadly adopted so that the future of the field may provide the greatest benefits to society.

Safety by design: Biosafety and biosecurity in the age of synthetic genomics.

Technologies to profoundly engineer biology are becoming increasingly affordable, powerful, and accessible to a widening group of actors. While offering tremendous potential to fuel biological research and the bioeconomy, this development also increases the risk of inadvertent or deliberate creation and dissemination of pathogens. Effective regulatory and technological frameworks need to be developed and deployed to manage these emerging biosafety and biosecurity risks. Here, we review digital and biological approaches of a range of technology readiness levels suited to address these challenges. Digital sequence screening technologies already are used to control access to synthetic DNA of concern. We examine the current state of the art of sequence screening, challenges and future directions, and environmental surveillance for the presence of engineered organisms. As biosafety layer on the organism level, we discuss genetic biocontainment systems that can be used to created host organisms with an intrinsic barrier against unchecked environmental proliferation.

Making Security Viral: Shifting Engineering Biology Culture and Publishing.

The ability to construct, synthesize, and edit genes and genomes at scale and with speed enables, in synergy with other tools of engineering biology, breakthrough applications with far-reaching implications for society. As SARS-CoV-2 spread around the world in early spring of 2020, researchers rapidly mobilized, using these tools in the development of diagnostics, therapeutics, and vaccines for COVID-19. The sharing of knowledge was crucial to making rapid progress. Several publications described the use of reverse genetics for the de novo construction of SARS-CoV-2 in the laboratory, one in the form of a protocol. Given the demonstrable harm caused by the virus, the unequal distribution of mitigating vaccines and therapeutics, their unknown efficacy against variants, and the interest in this research by laboratories unaccustomed to working with highly transmissible pandemic pathogens, there are risks associated with such publications, particularly as protocols. We describe considerations and offer suggestions for enhancing security in the publication of synthetic biology research and techniques. We recommend: (1) that protocol manuscripts for the de novo synthesis of certain pathogenic viruses undergo a mandatory safety and security review; (2) that if published, such papers include descriptions of the discussions or review processes that occurred regarding security considerations in the main text; and (3) the development of a governance framework for the inclusion of basic security screening during the publication process of engineering biology/synthetic biology manuscripts to build and support a safe and secure research enterprise that is able to maximize its positive impacts and minimize any negative outcomes.

Guiding Ethical Principles in Engineering Biology Research.

Engineering biology is being applied toward solving or mitigating some of the greatest challenges facing society. As with many other rapidly advancing technologies, the development of these powerful tools must be considered in the context of ethical uses for personal, societal, and/or environmental advancement. Researchers have a responsibility to consider the diverse outcomes that may result from the knowledge and innovation they contribute to the field. Together, we developed a Statement of Ethics in Engineering Biology Research to guide researchers as they incorporate the consideration of long-term ethical implications of their work into every phase of the research lifecycle. Herein, we present and contextualize this Statement of Ethics and its six guiding principles. Our goal is to facilitate ongoing reflection and collaboration among technical researchers, social scientists, policy makers, and other stakeholders to support best outcomes in engineering biology innovation and development.

Next Steps to Grow the Bioeconomy.

The bioeconomy in the United States represents a significant proportion of total economic output and is poised to grow even more rapidly over the next decade. Global competition is increasing, and the United States must work to ensure we maintain global leadership in this field. In this commentary, we outline policy recommendations in 6 topic areas. Taken together, these recommendations call on government, academia, and private industry to collaborate, both domestically and internationally, to grow and secure the current and future bioeconomy in the United States.

Next Steps for Access to Safe, Secure DNA Synthesis.

The DNA synthesis industry has, since the invention of gene-length synthesis, worked proactively to ensure synthesis is carried out securely and safely. Informed by guidance from the U.S. government, several of these companies have collaborated over the last decade to produce a set of best practices for customer and sequence screening prior to manufacture. Taken together, these practices ensure that synthetic DNA is used to advance research that is designed and intended for public benefit. With increasing scale in the industry and expanding capability in the synthetic biology toolset, it is worth revisiting current practices to evaluate additional measures to ensure the continued safety and wide availability of DNA synthesis. Here we encourage specific steps, in part derived from successes in the cybersecurity community, that can ensure synthesis screening systems stay well ahead of emerging challenges, to continue to enable responsible research advances. Gene synthesis companies, science and technology funders, policymakers, and the scientific community as a whole have a shared duty to continue to minimize risk and maximize the safety and security of DNA synthesis to further power world-changing developments in advanced biological manufacturing, agriculture, drug development, healthcare, and energy.

Defining the Synthetic Biology Supply Chain.

Several recent articles have described risks posed by synthetic biology and spurred vigorous discussion in the scientific, commercial, and government communities about how to best detect, prevent, regulate, and respond to these risks. The Pacific Northwest National Laboratory's (PNNL) deep experience working with dual-use technologies for the nuclear industry has shown that analysis of supply chains can reveal security vulnerabilities and ways to mitigate security risk without hindering beneficial research and commerce. In this article, a team of experts in synthetic biology, data analytics, and national security describe the overall supply chain surrounding synthetic biology to illustrate new insights about the effectiveness of current regulations, the possible need for different screening approaches, and new technical solutions that could help identify or mitigate risks in the synthetic biology supply chain.

Classification of usual interstitial pneumonia in patients with interstitial lung disease: assessment of a machine learning approach using high-dimensional transcriptional data.

BACKGROUND: Idiopathic pulmonary fibrosis is a progressive fibrotic lung disease that distorts pulmonary architecture, leading to hypoxia, respiratory failure, and death. Diagnosis is difficult because other interstitial lung diseases have similar radiological and histopathological characteristics. A usual interstitial pneumonia pattern is a hallmark of idiopathic pulmonary fibrosis and is essential for its diagnosis. We aimed to develop a molecular test that distinguishes usual interstitial pneumonia from other interstitial lung diseases in surgical lung biopsy samples. The eventual goal of this research is to develop a method to diagnose idiopathic pulmonary fibrosis without the patient having to undergo surgery. METHODS: We collected surgical lung biopsy samples from patients with various interstitial lung diseases at 11 hospitals in North America. Pathology diagnoses were confirmed by an expert panel. We measured RNA expression levels for 33 297 transcripts on microarrays in all samples. A classifier algorithm was trained on one set of samples and tested in a second set. We subjected a subset of samples to next-generation RNA sequencing (RNAseq) generating expression levels on 55 097 transcripts, and assessed a classifier trained on RNAseq data by cross-validation. FINDINGS: We took 125 surgical lung biopsies from 86 patients. 58 samples were identified by the expert panel as usual interstitial pneumonia, 23 as non-specific interstitial pneumonia, 16 as hypersensitivity pneumonitis, four as sarcoidosis, four as respiratory bronchiolitis, two as organising pneumonia, and 18 as subtypes other than usual interstitial pneumonia. The microarray classifier was trained on 77 samples and was assessed in a test set of 48 samples, for which it had a specificity of 92% (95% CI 81-100) and a sensitivity of 82% (64-95). Based on a subset of 36 samples, the RNAseq classifier had a specificity of 95% (84-100) and a sensitivity of 59% (35-82). INTERPRETATION: Our results show that the development of a genomic signature that predicts usual interstitial pneumonia is feasible. These findings are an important first step towards the development of a molecular test that could be applied to bronchoscopy samples, thus avoiding surgery in the diagnosis of idiopathic pulmonary fibrosis. FUNDING: Veracyte.

Machine learning from concept to clinic: reliable detection of BRAF V600E DNA mutations in thyroid nodules using high-dimensional RNA expression data.

The promise of personalized medicine will require rigorously validated molecular diagnostics developed on minimally invasive, clinically relevant samples. Measurement of DNA mutations is increasingly common in clinical settings but only higher-prevalence mutations are cost-effective. Patients with rare variants are at best ignored or, at worst, misdiagnosed. Mutations result in downstream impacts on transcription, offering the possibility of broader diagnosis for patients with rare variants causing similar downstream changes. Use of such signatures in clinical settings is rare as these algorithms are difficult to validate for commercial use. Validation on a test set (against a clinical gold standard) is necessary but not sufficient: accuracy must be maintained amidst interfering substances, across reagent lots and across operators. Here we report the development, clinical validation, and diagnostic accuracy of a pre-operative molecular test (Afirma BRAF) to identify BRAF V600E mutations using mRNA expression in thyroid fine needle aspirate biopsies (FNABs). FNABs were obtained prospectively from 716 nodules and more than 3,000 features measured using microarrays. BRAF V600E labels for training (n=181) and independent test (n=535) sets were established using a sensitive quantitative PCR (qPCR) assay. The resulting 128-gene linear support vector machine was compared to qPCR in the independent test set. Clinical sensitivity and specificity for malignancy were evaluated in a subset of test set samples (n=213) with expert-derived histopathology. We observed high positive- (PPA, 90.4%) and negative (NPA, 99.0%) percent agreement with qPCR on the test set. Clinical sensitivity for malignancy was 43.8% (consistent with published prevalence of BRAF V600E in this neoplasm) and specificity was 100%, identical to qPCR on the same samples. Classification was accurate in up to 60% blood. A double-mutant still resulting in the V600E amino acid change was negative by qPCR but correctly positive by Afirma BRAF. Non-diagnostic rates were lower (7.6%) for Afirma BRAF than for qPCR (24.5%), a further advantage of using RNA in small sample biopsies. Afirma BRAF accurately determined the presence or absence of the BRAF V600E DNA mutation in FNABs, a collection method directly relevant to solid tumor assessment, with performance equal to that of an established, highly sensitive DNA-based assay and with a lower non-diagnostic rate. This is the first such test in thyroid cancer to undergo sufficient analytical and clinical validation for real-world use in a personalized medicine context to frame individual patient risk and inform surgical choice.

A prospective assessment defining the limitations of thyroid nodule pathologic evaluation.

BACKGROUND: Clinical management of thyroid neoplasms is based on light microscopic diagnosis, but its accuracy and precision are poorly defined. OBJECTIVE: To assess inter- and intraobserver variability of preoperative cytopathologic and postoperative histopathologic thyroid diagnoses. DESIGN: Samples were collected in a prospective, multicenter trial validating a gene expression classifier between June 2009 and December 2010. SETTING: 14 academic and 35 community clinical sites. PATIENTS: 653 patients with 776 surgically resected thyroid nodules of 1 cm or greater. MEASUREMENTS: Intraobserver concordance among 2 or more central histopathologists who independently read histopathology slides was calculated. Interobserver concordance between the diagnoses made by the central histopathologists and those made by local pathologists were calculated. Intra- and interobserver concordance for cytopathology was similarly calculated by comparing diagnoses made by local pathologists with those made by a central panel of 3 cytopathologists. RESULTS: Concordance on the histopathologic distinction between benign and malignant diagnoses was 91% comparing local with central histopathologists and 90% comparing 2 central histopathologists. Using the 6-category Bethesda System, 64.0% of diagnoses made by local and central cytopathologists and 74.7% of intraobserver diagnoses were concordant. Central cytopathologists made fewer indeterminate diagnoses than local pathologists (41.2% vs. 55.0%). LIMITATIONS: Many local pathologists did not use the Bethesda System, so their reports were translated to allow comparison. The study required histopathology, and the study population and specimens did not encompass all newly evaluated patients with a thyroid nodule. CONCLUSION: Substantial inter- and intraobserver variability exists in the cytopathologic and histopathologic evaluation of thyroid nodules, confirming an inherent limitation of visual microscopic diagnosis. PRIMARY FUNDING SOURCE: Veracyte.

The impact of benign gene expression classifier test results on the endocrinologist-patient decision to operate on patients with thyroid nodules with indeterminate fine-needle aspiration cytopathology.

BACKGROUND: Seventy-five percent of thyroid nodules with indeterminate fine-needle aspiration (FNA) cytology are found to be benign postoperatively. A novel genomic test, the Afirma gene expression classifier (AGEC), has been available for clinical use in the United States, since late 2010. In 2010, two modest-sized validation studies showed that the AGEC could identify a benign gene expression signature in indeterminate cytology thyroid FNA samples with a negative predictive value >95%. The objective of this study was to evaluate how the AGEC impacted the joint decision of the endocrinologist and patient to operate when FNA cytology was indeterminate, but the AGEC reading of the nodule was benign. METHODS: In this cross-sectional cohort study, data were contributed retrospectively by 51 endocrinologists at 21 practice sites that had previously obtained ≥3 benign AGEC readings in ≥1 cm nodules with indeterminate FNA cytology readings. Information regarding demographic data, nodule size and location, decision to operate, surgery type (hemithyroidectomy [HT] or total thyroidectomy [TT]), and reason for recommending surgery was retrospectively collected. RESULTS: Compared to a 74% previous historical rate of surgery for cytologically indeterminate nodules, the operative rate fell to 7.6% during the period that AGEC were obtained in the clinical practices, a highly significant reduction in the decision to operate (p<0.001). The rate of surgery on cytologically indeterminate nodules that were benign by the AGEC reading did not differ from the historically reported rate of operation on cytologically benign nodules (p=0.41). The four primary reasons reported by the physicians for operating on nodules with a benign AGEC reading, in descending order: large nodule size (46.4%), symptomatic nodules (25.0%), rapidly growing nodules (10.7%), or a second suspicious or malignant nodule in the same patient (10.7%). These reasons are concordant with those typically given for operation on cytologically benign nodules. CONCLUSIONS: In a substantial group of medical practices, obtaining an AGEC test in patients with cytologically indeterminate nodules was associated with a striking reduction in the rate of diagnostic thyroidectomy. Approximately, one surgery was avoided for every two AGEC tests run on thyroid FNAs with indeterminate cytology.

Preoperative diagnosis of benign thyroid nodules with indeterminate cytology.

BACKGROUND: Approximately 15 to 30% of thyroid nodules evaluated by means of fine-needle aspiration are not clearly benign or malignant. Patients with cytologically indeterminate nodules are often referred for diagnostic surgery, though most of these nodules prove to be benign. A novel diagnostic test that measures the expression of 167 genes has shown promise in improving preoperative risk assessment. METHODS: We performed a 19-month, prospective, multicenter validation study involving 49 clinical sites, 3789 patients, and 4812 fine-needle aspirates from thyroid nodules 1 cm or larger that required evaluation. We obtained 577 cytologically indeterminate aspirates, 413 of which had corresponding histopathological specimens from excised lesions. Results of a central, blinded histopathological review served as the reference standard. After inclusion criteria were met, a gene-expression classifier was used to test 265 indeterminate nodules in this analysis, and its performance was assessed. RESULTS: Of the 265 indeterminate nodules, 85 were malignant. The gene-expression classifier correctly identified 78 of the 85 nodules as suspicious (92% sensitivity; 95% confidence interval [CI], 84 to 97), with a specificity of 52% (95% CI, 44 to 59). The negative predictive values for "atypia (or follicular lesion) of undetermined clinical significance," "follicular neoplasm or lesion suspicious for follicular neoplasm," or "suspicious cytologic findings" were 95%, 94%, and 85%, respectively. Analysis of 7 aspirates with false negative results revealed that 6 had a paucity of thyroid follicular cells, suggesting insufficient sampling of the nodule. CONCLUSIONS: These data suggest consideration of a more conservative approach for most patients with thyroid nodules that are cytologically indeterminate on fine-needle aspiration and benign according to gene-expression classifier results. (Funded by Veracyte.).

Open-target sparse sensing of biological agents using DNA microarray.

BACKGROUND: Current biosensors are designed to target and react to specific nucleic acid sequences or structural epitopes. These 'target-specific' platforms require creation of new physical capture reagents when new organisms are targeted. An 'open-target' approach to DNA microarray biosensing is proposed and substantiated using laboratory generated data. The microarray consisted of 12,900 25 bp oligonucleotide capture probes derived from a statistical model trained on randomly selected genomic segments of pathogenic prokaryotic organisms. Open-target detection of organisms was accomplished using a reference library of hybridization patterns for three test organisms whose DNA sequences were not included in the design of the microarray probes. RESULTS: A multivariate mathematical model based on the partial least squares regression (PLSR) was developed to detect the presence of three test organisms in mixed samples. When all 12,900 probes were used, the model correctly detected the signature of three test organisms in all mixed samples (mean(R²)) = 0.76, CI = 0.95), with a 6% false positive rate. A sampling algorithm was then developed to sparsely sample the probe space for a minimal number of probes required to capture the hybridization imprints of the test organisms. The PLSR detection model was capable of correctly identifying the presence of the three test organisms in all mixed samples using only 47 probes (mean(R²)) = 0.77, CI = 0.95) with nearly 100% specificity. CONCLUSIONS: We conceived an 'open-target' approach to biosensing, and hypothesized that a relatively small, non-specifically designed, DNA microarray is capable of identifying the presence of multiple organisms in mixed samples. Coupled with a mathematical model applied to laboratory generated data, and sparse sampling of capture probes, the prototype microarray platform was able to capture the signature of each organism in all mixed samples with high sensitivity and specificity. It was demonstrated that this new approach to biosensing closely follows the principles of sparse sensing.