Automation of a multiplex agglutination-PCR (ADAP) type 1 diabetes (T1D) assay for the rapid analysis of islet autoantibodies.

Screening for islet autoantibody markers to identify individuals who are at high risk for developing type 1 diabetes (T1D), often years in advance of clinical symptoms, is both a challenge and a necessity. Identifying high-risk individuals not only reduces hospitalization and rates of life-threatening diabetes ketoacidosis (DKA), but also directs enrollment into prevention trials that require patients who are in the early stages of disease. Here we describe an automated high-throughput multiplex islet autoantibody assay that integrates antibody detection by agglutination-PCR (ADAP) chemistry on the Hamilton Microlab STAR liquid handling platform. The automated system features on-deck thermal cycling and plate sealing to minimize the level of human intervention. The automated multiplex ADAP T1D assay performed similarly to that of manual methods using two distinct cohorts of clinical specimens obtained from the Lucile Packard Children's Hospital at Stanford University and the 2018 Islet Autoantibody Standardization Program (IASP). Notably, the automated assay requires only 4 µL of serum sample for the simultaneous analysis of GAD, IA-2 and insulin autoantibodies. Up to 96 samples may be processed in as little as 3 hours, and the only user intervention required is to transfer a final sealed 96-well plate containing PCR amplicons onto a quantitative PCR (RT-qPCR) instrument for quantification. The automated system is particularly well suited for large-scale analysis of islet autoantibodies in a reproducible, timely, and cost-effective manner.

Fast Discrimination of Marijuana using Automated High-throughput Cannabis Sample Preparation and Analysis by Gas Chromatography-Mass Spectrometry.

In the United States, federal law and many state laws differentiate between marijuana and industrial hemp through delta-9-tetrahydrocannabinol (THC) levels, whereby the latter is defined as ≤0.3 percent THC on a dry weight basis. Many traditional cannabis identification methods employed by crime laboratories cannot accurately determine total THC quantities in accordance with federal and state regulations, or do so with increased time, labor, and risks of instrument damage. In order to quickly distinguish positive marijuana samples, a method was developed to identify plant material with a total THC level >1%. This novel, automated dispersive pipette extraction (DPX) method uses tip-based technology and an automated liquid handler to enable fast, hands-free selective isolation of THC and its precursors for downstream gas chromatography-mass spectrometry (GC-MS) analysis. The workflow proceeds with no repetitive manual effort and reduced need for instrument maintenance while enabling crime labs to legally identify marijuana through the detection of total THC above 1%. Recovery of THC using the DPX extraction method was 93% at 30 µg/mL and 78% at 500 µg/mL. Similarly, THCA-A recovery was 100% at 30 µg/mL and 74% at 500 µg/mL. Samples evaluated in a blind study (proficiency, hemp, and nonprobative case samples) were all accurately identified as greater than or less than 1% THC, with samples containing <1% THC being identified as "cannabis" and subjected to more discriminative analysis as needed.

A Semi-Automated Tuberculosis Testing Workflow Reduces Manual Hazardous Sample Handling and Hands-On Time: A Proof-of-Concept Study.

A central tenet of good diagnostic laboratory practice is protecting laboratory staff from contact with sample-borne pathogens and dangerous chemicals. Automated sample-processing systems can reduce or eliminate the risk of exposure to infectious samples while providing results on par with, or better than, those from manually processed samples. In addition, hands-free automated processing may enable analysts to focus on higher order activities while eliminating the risk of repetitive strain injuries associated with manual pipetting. Here, we describe a semi-automated tuberculosis interferon-γ release assay (IGRA) workflow that includes an automated high-throughput sample-processing system. The system automates cap removal, automates sample mixing and aspiration of blood from lithium heparin collection tubes, and aliquots blood samples into multiple blood assay tubes for downstream testing without manual intervention. We show that automated results are comparable to manual methods without risk of analyst exposure or repetitive strain injury.

Sensitive and Specific Detection of SARS-CoV-2 Antibodies Using a High-Throughput, Fully Automated Liquid-Handling Robotic System.

As of July 22, 2020, more than 14.7 million infections of SARS-CoV-2, the virus responsible for Coronavirus Disease 2019 (COVID-19), have been confirmed globally. Serological assays are essential for community screening, assessing infection prevalence, aiding identification of infected patients, and enacting appropriate treatment and quarantine protocols in the battle against this rapidly expanding pandemic. Antibody detection by agglutination-PCR (ADAP) is a pure solution phase immunoassay that generates a PCR amplifiable signal when patient antibodies agglutinate DNA-barcoded antigen probes into a dense immune complex. Here, we present an ultrasensitive and high-throughput automated liquid biopsy assay based on the Hamilton Microlab ADAP STAR automated liquid-handling platform, which was developed and validated for the qualitative detection of total antibodies against spike protein 1 (S1) of SARS-CoV-2 that uses as little as 4 µL of serum. To assess the clinical performance of the ADAP assay, 57 PCR-confirmed COVID-19 patients and 223 control patients were tested. The assay showed a sensitivity of 98% (56/57) and a specificity of 99.55% (222/223). Notably, the SARS-CoV-2-negative control patients included individuals with other common coronaviral infections, such as CoV-NL63 and CoV-HKU, which did not cross-react. In addition to high performance, the hands-free automated workstation enabled high-throughput sample processing to reduce screening workload while helping to minimize analyst contact with biohazardous samples. Therefore, the ADAP STAR liquid-handling workstation can be used as a valuable tool to address the COVID-19 global pandemic.

A Novel, Automated Dispersive Pipette Extraction Technology Greatly Simplifies Catecholamine Sample Preparation for Downstream LC-MS/MS Analysis.

Catecholamines are integral neurotransmitters in the central and peripheral nervous system. Clinically, catecholamine levels are determined to help diagnose disease and measure corresponding therapeutic effectiveness. However, manual extraction of catecholamines and their metabolites may be labor-intensive and user-variable and require a variety of peripheral laboratory devices, especially at low sample concentrations. Here, we propose a novel solid-phase extraction (SPE) method using patented dispersive pipette extraction (DPX) tip technology. The tips are readily integrated into an automated workflow to extract these compounds from urine, which increases analytical throughput while removing human variability and error. Diphenylboronic acid (DPBA) forms a stable, negatively charged complex with catecholamines in the samples, and when aspirated into the DPX tip, the complexed analytes are retained on a styrene divinyl benzene sorbent. Wash buffers remove interfering compounds, after which the complex is eluted from the tip using an acidic aqueous solution and subsequently measured via liquid chromatography with tandem mass spectrometry (LC-MS/MS). The automated DPX method for catecholamine sample preparation from urine has excellent linearity over more than three orders of magnitude with concentrations ranging from 0.5 to 1000 ng/mL, with replicate analyses resulting in coefficients of variation of less than 8%. This high-throughput workflow is appropriate for use in regulated laboratories.

Automation of the standard DNA differential extraction on the Hamilton AutoLys STAR system: A proof-of-concept study.

For several decades, a common approach for processing sexual assault evidence has been to use the "standard" differential extraction to separate the evidence into a non-sperm-cell fraction and a sperm-cell fraction for further analysis. In this standard approach (P. Gill et al., Nature 318 (1985) 577-579), an initial mild chemical lysis step preferentially digests the mainly epithelial cells, which allows for removing this lysate as a non-sperm-cell fraction. The undigested sperm cells in the remaining fraction may then be purified by a series of wash and centrifugation steps, after which more robust lysis conditions are used to digest this sperm-cell fraction. Although this standard approach has been generally effective, it has been difficult to fully automate, due to the variety of different types of manipulations required for sample processing (e.g., incubation, shaking, substrate separation by centrifugation, and multiple liquid transfers for sperm-pellet centrifugation and washing steps). We describe here a fully automated standard differential extraction procedure that uses the Hamilton AutoLys STAR liquid handling assay-ready workstation, which is configured with on-deck components for sample incubation, shaking and centrifugation steps, and works with unique AutoLys-A® sample tubes for front-end sample processing. In this proof-of-concept procedure, up to 24 samples may be processed, "hands-free," in a single automated workflow. The automated procedure was tested by performing differential extractions on mock sexual assault swabs. For comparison, manual differential extractions were performed on identically prepared swabs in a side-by-side manner. DNA quantification and STR typing results showed that similar levels of separation efficiency were achieved for the sperm-cell fractions using both automated and manual procedures, although the results suggest that somewhat higher male DNA yields may be achieved for samples with extremely low semen levels (<∼0.1 µL) using the manual processing procedure. In addition to these mock samples, automated differential extractions were also performed on a set of authentic post-coital swabs (24, 48, 72, and 96 hours, post-coitus); primarily male STR profiles for the sperm-cell fractions were obtained for each sample in this set.

TrueAllele(®) Genotype Identification on DNA Mixtures Containing up to Five Unknown Contributors.

Computer methods have been developed for mathematically interpreting mixed and low-template DNA. The genotype modeling approach computationally separates out the contributors to a mixture, with uncertainty represented through probability. Comparison of inferred genotypes calculates a likelihood ratio (LR), which measures identification information. This study statistically examined the genotype modeling performance of Cybergenetics TrueAllele(®) computer system. High- and low-template DNA mixtures of known randomized composition containing 2, 3, 4, and 5 contributors were tested. Sensitivity, specificity, and reproducibility were established through LR quantification in each of these eight groups. Covariance analysis found LR behavior to be relatively invariant to DNA amount or contributor number. Analysis of variance found that consistent solutions were produced, once a sufficient number of contributors were considered. This study demonstrates the reliability of TrueAllele interpretation on complex DNA mixtures of representative casework composition. The results can help predict an information outcome for a DNA mixture analysis.

Recommendations for consistent treatment of length variants in the human mitochondrial DNA control region.

Human mitochondrial DNA (mtDNA) analysis is a valuable forensic tool, useful in cases where the amount of extracted DNA is low or highly degraded. Population databases are used to determine the relative rarity of a particular profile obtained in a forensic case. Rather than full DNA sequence information, sequence profiles are compared to a reference sequence, and the differences from the reference are recorded in forensic databases. A standard method is proposed for characterizing length variants, and examples are described using actual human control region mtDNA profiles. Consistency in alignment and nomenclature avoids inadvertently describing two sequences as different when in fact they are the same.

Developmental validation of RSID™-Semen: a lateral flow immunochromatographic strip test for the forensic detection of human semen.

Tests for the identification of semen commonly involve the microscopic visualization of spermatozoa or assays for the presence of seminal markers such as acid phosphatase (AP) or prostate-specific antigen (PSA). Here, we describe the rapid stain identification kit for the identification of semen (RSID™-Semen), a lateral flow immunochromatographic strip test that uses two antihuman semenogelin monoclonal antibodies to detect the presence of semenogelin. The RSID™-Semen strip is specific for human semen, detecting <2.5 nL of semen, and does not cross-react with other human or nonhuman tissues tested. RSID™-Semen is more sensitive with certain forensic evidence samples containing mixtures of vaginal secretions and semen than either of the commercially available PSA-based forensic semen detection tests or tests that measure AP activity that were tested in parallel. The RSID™-Semen kit also allows sampling a fraction of a questioned stain while retaining the majority of the sample for further processing through short tandem repeat analysis.

Identification of group affinity from cross-sectional contours of the human midfacial skeleton using digital morphometrics and 3D laser scanning technology.

Identifying group affinity from human crania is a long-standing problem in forensic and physical anthropology. Many craniofacial differences used in forensic skeletal identification are difficult to quantify, although certain measurements of the midfacial skeleton have shown high predictive value for group classifications. This study presents a new method for analyzing midfacial shape variation between different geographic groups. Three-dimensional laser scan models of 90 crania from three populations were used to obtain cross-sectional midfacial contours defined by three standard craniometric landmarks. Elliptic Fourier transforms of the contours were used to extract Fourier coefficients for statistical analysis. After cross-validation, discriminant functions based on the Fourier coefficients provided an average of 86% correct classifications for crania from the three groups. The high rate of accuracy of this method indicates its usefulness for identifying group affinities among human skeletal remains and demonstrates the advantages of digital 3D model-based analysis in forensic research.

Developmental validation of the SPERM HY-LITER™ kit for the identification of human spermatozoa in forensic samples.

With sexual assault evidence, the visualization of spermatozoa confirms that ejaculation has occurred. However, microscopic examination of spermatozoa is a laborious process and can sometimes result in sperm cells being overlooked. Here, we present the developmental validation of the SPERM HY-LITER™ kit, which contains a human sperm-specific mouse monoclonal antibody coupled to a fluorescent Alexa 488 dye. The kit was tested using samples of human semen, saliva, blood, and urine, various animal semen extracts, sexual lubricants, and a commercially available spermicidal film. Postcoital vaginal swabs, degraded semen samples, and samples prepared with sample fixation techniques that deviated from the kit-provided protocol were also tested. In each case, the SPERM HY-LITER™ kit was demonstrated to bind only to human sperm cell heads. Limitations to this fluorescent staining procedure include nonspecific staining and increased background fluorescence with extreme heat fixation in some samples.

Variation in the measurement of cranial volume and surface area using 3D laser scanning technology.

Three-dimensional (3D) laser scanner models of human crania can be used for forensic facial reconstruction, and for obtaining craniometric data useful for estimating age, sex, and population affinity of unidentified human remains. However, the use of computer-generated measurements in a casework setting requires the measurement precision to be known. Here, we assess the repeatability and precision of cranial volume and surface area measurements using 3D laser scanner models created by different operators using different protocols for collecting and processing data. We report intraobserver measurement errors of 0.2% and interobserver errors of 2% of the total area and volume values, suggesting that observer-related errors do not pose major obstacles for sharing, combining, or comparing such measurements. Nevertheless, as no standardized procedure exists for area or volume measurements from 3D models, it is imperative to report the scanning and postscanning protocols employed when such measurements are conducted in a forensic setting.

SNPsFinder--a web-based application for genome-wide discovery of single nucleotide polymorphisms in microbial genomes.

UNLABELLED: Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variations in closely related microbial species, strains or isolates. Some SNPs confer selective advantages for microbial pathogens during infection and many others are powerful genetic markers for distinguishing closely related strains or isolates that could not be distinguished otherwise. To facilitate SNP discovery in microbial genomes, we have developed a web-based application, SNPsFinder, for genome-wide identification of SNPs. SNPsFinder takes multiple genome sequences as input to identify SNPs within homologous regions. It can also take contig sequences and sequence quality scores from ongoing sequencing projects for SNP prediction. SNPsFinder will use genome sequence annotation if available and map the predicted SNP regions to known genes or regions to assist further evaluation of the predicted SNPs for their functional significance. SNPsFinder can generate PCR primers for all predicted SNP regions according to user's input parameters to facilitate experimental validation. The results from SNPsFinder analysis are accessible through the World Wide Web. AVAILABILITY: The SNPsFinder program is available at http://snpsfinder.lanl.gov/. SUPPLEMENTARY INFORMATION: The user's manual is available at http://snpsfinder.lanl.gov/UsersManual/

HVI and HVII mitochondrial DNA data in Apaches and Navajos.

Most mtDNA studies on Native Americans have concentrated on hypervariable region I (HVI) sequence data. Mitochondrial DNA haplotype data from hypervariable regions I and II (HVI and HVII) have been compiled from Apaches (N=180) and Navajos (N=146). The inclusion of HVII data increases the amount of information that can be obtained from low diversity population groups. Less mtDNA variation was observed in the Apaches and Navajos than in major population groups. The majority of the mtDNA sequences were observed more than once; only 17.8% (32/180) of the Apache sequences and 25.8% of the Navajo sequences were observed once. Most of the haplotypes in Apaches and Navajos fall into the A and B haplogroups. Although a limited number of haplogroups were observed, both sample populations exhibit sufficient variation for forensic mtDNA typing. Genetic diversity was 0.930 in the Apache sample and 0.963 in the Navajo sample. The random match probability was 7.48% in the Apache sample and 4.40% in the Navajo sample. The average number of nucleotide differences between individuals in a database is 9.0 in the Navajo sample and 7.7 in the Apache sample. The data demonstrate that mtDNA sequencing can be informative in forensic cases where Native American population data are used.