HLA Class II (DR, DQ, DP) Genes Were Separately Associated With the Progression From Seroconversion to Onset of Type 1 Diabetes Among Participants in Two Diabetes Prevention Trials (DPT-1 and TN07).

OBJECTIVE: To explore associations of HLA class II genes (HLAII) with the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: Next-generation targeted sequencing was used to genotype eight HLAII genes (DQA1, DQB1, DRB1, DRB3, DRB4, DRB5, DPA1, DPB1) in 1,216 participants from the Diabetes Prevention Trial-1 and Randomized Diabetes Prevention Trial with Oral Insulin sponsored by TrialNet. By the linkage disequilibrium, DQA1 and DQB1 are haplotyped to form DQ haplotypes; DP and DR haplotypes are similarly constructed. Together with available clinical covariables, we applied the Cox regression model to assess HLAII immunogenic associations with the disease progression. RESULTS: First, the current investigation updated the previously reported genetic associations of DQA1*03:01-DQB1*03:02 (hazard ratio [HR] = 1.25, P = 3.50*10-3) and DQA1*03:03-DQB1*03:01 (HR = 0.56, P = 1.16*10-3), and also uncovered a risk association with DQA1*05:01-DQB1*02:01 (HR = 1.19, P = 0.041). Second, after adjusting for DQ, DPA1*02:01-DPB1*11:01 and DPA1*01:03-DPB1*03:01 were found to have opposite associations with progression (HR = 1.98 and 0.70, P = 0.021 and 6.16*10-3, respectively). Third, DRB1*03:01-DRB3*01:01 and DRB1*03:01-DRB3*02:02, sharing the DRB1*03:01, had opposite associations (HR = 0.73 and 1.44, P = 0.04 and 0.019, respectively), indicating a role of DRB3. Meanwhile, DRB1*12:01-DRB3*02:02 and DRB1*01:03 alone were found to associate with progression (HR = 2.6 and 2.32, P = 0.018 and 0.039, respectively). Fourth, through enumerating all heterodimers, it was found that both DQ and DP could exhibit associations with disease progression. CONCLUSIONS: These results suggest that HLAII polymorphisms influence progression from islet autoimmunity to T1D among at-risk subjects with islet autoantibodies.

Genotyping of canine MHC gene DLA-88 by next-generation sequencing reveals high frequencies of new allele discovery and gene duplication.

Dogs have served as one of the most reliable preclinical models for a variety of diseases and treatments, including stem/progenitor cell transplantation. At the genetic epicenter of dog transplantation models, polymorphic major histocompatibility complex (MHC) genes are most impactful on transplantation success. Among the canine class I and class II genes, DLA-88 has been best studied in transplantation matching and outcomes, with 129 DLA-88 alleles identified. In this study we developed and tested a next generation (NGS) sequencing protocol for rapid identification of DLA-88 genotypes in dogs and compared the workflow and data generated with an established DLA-88 Sanger sequencing protocol that has been in common prior use for clinical studies. By testing the NGS protocol on a random population of 382 dogs, it was possible to demonstrate superior efficacy based on laboratory execution and overall cost. In addition, NGS proved far more effective at discovering new alleles and detecting multiple alleles associated with gene duplication. A total of 51 new DLA-88 alleles are reported here. This rate of new allele discovery indicates that a large pool of yet un-discovered DLA-88 alleles exists in the domestic dog population. In addition, more than 46% of dogs carried three or more copies of DLA-88, further emphasizing the need for more sensitive and cost-effective DLA typing methodology for the dog clinical model.

Association of HLA-DQ Heterodimer Residues -18ß and ß57 With Progression From Islet Autoimmunity to Diabetes in the Diabetes Prevention Trial-Type 1.

OBJECTIVE: The purpose was to test the hypothesis that the HLA-DQαß heterodimer structure is related to the progression of islet autoimmunity from asymptomatic to symptomatic type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: Next-generation targeted sequencing was used to genotype HLA-DQA1-B1 class II genes in 670 subjects in the Diabetes Prevention Trial-Type 1 (DPT-1). Coding sequences were translated into DQ α- and ß-chain amino acid residues and used in hierarchically organized haplotype (HOH) association analysis to identify motifs associated with diabetes onset. RESULTS: The opposite diabetes risks were confirmed for HLA DQA1*03:01-B1*03:02 (hazard ratio [HR] 1.36; P = 2.01 ∗ 10-3) and DQA1*03:03-B1*03:01 (HR 0.62; P = 0.037). The HOH analysis uncovered residue -18ß in the signal peptide and ß57 in the ß-chain to form six motifs. DQ*VA was associated with faster (HR 1.49; P = 6.36 ∗ 10-4) and DQ*AD with slower (HR 0.64; P = 0.020) progression to diabetes onset. VA/VA, representing DQA1*03:01-B1*03:02 (DQ8/8), had a greater HR of 1.98 (P = 2.80 ∗ 10-3). The DQ*VA motif was associated with both islet cell antibodies (P = 0.023) and insulin autoantibodies (IAAs) (P = 3.34 ∗ 10-3), while the DQ*AD motif was associated with a decreased IAA frequency (P = 0.015). Subjects with DQ*VA and DQ*AD experienced, respectively, increasing and decreasing trends of HbA1c levels throughout the follow-up. CONCLUSIONS: HLA-DQ structural motifs appear to modulate progression from islet autoimmunity to diabetes among at-risk relatives with islet autoantibodies. Residue -18ß within the signal peptide may be related to levels of protein synthesis and ß57 to stability of the peptide-DQab trimolecular complex.

Mutations in viral nucleocapsid protein and endoRNase are discovered to associate with COVID19 hospitalization risk.

SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients; 388 inpatients ("cases") and 295 outpatients ("controls") from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes. To improve the analytical power, we accessed 7137 viral sequences in Washington State to filter out viral single nucleotide variants (SNVs) that did not have significant expansions over the collection period. Applying this filter led to the identification of 53 SNVs that were statistically significant, of which 13 SNVs each had 3 or more variant copies in the discovery cohort. Correlating these selected SNVs with case/control status, eight SNVs were found to significantly associate with inpatient status (q-values < 0.01). Using temporal synchrony, we identified a four SNV-haplotype (t19839-g28881-g28882-g28883) that was significantly associated with case/control status (Fisher's exact p = 2.84 × 10-11). This haplotype appeared in April 2020, peaked in June, and persisted into January 2021. The association was replicated (OR = 5.46, p-value = 4.71 × 10-12) in an independent cohort of 964 COVID-19 patients (June 1, 2020 to March 31, 2021). The haplotype included a synonymous change N73N in endoRNase, and three non-synonymous changes coding residues R203K, R203S and G204R in the nucleocapsid protein. This discovery points to the potential functional role of the nucleocapsid protein in triggering "cytokine storms" and severe COVID-19 that led to hospitalization. The study further emphasizes a need for tracking and analyzing viral sequences in correlations with clinical status.

The KAG motif of HLA-DRB1 (ß71, ß74, ß86) predicts seroconversion and development of type 1 diabetes.

BACKGROUND: HLA-DR4, a common antigen of HLA-DRB1, has multiple subtypes that are strongly associated with risk of type 1 diabetes (T1D); however, some are risk neutral or resistant. The pathobiological mechanism of HLA-DR4 subtypes remains to be elucidated. METHODS: We used a population-based case-control study of T1D (962 patients and 636 controls) to decipher genetic associations of HLA-DR4 subtypes and specific residues with susceptibility to T1D. Using a birth cohort of 7865 children with periodically measured islet autoantibodies (GADA, IAA or IA-2A), we proposed to validate discovered genetic associations with a totally different study design and time-to-seroconversions prior to clinical onset of T1D. A novel analytic strategy hierarchically organized the HLA-DRB1 alleles by sequence similarity and identified critical amino acid residues by minimizing local genomic architecture and higher-order interactions. FINDINGS: Three amino acid residues of HLA-DRB1 (ß71, ß74, ß86) were found to be predictive of T1D risk in the population-based study. The "KAG" motif, corresponding to HLA-DRB1×04:01, was most strongly associated with T1D risk ([O]dds [R]atio=3.64, p = 3.19 × 10-64). Three less frequent motifs ("EAV", OR = 2.55, p = 0.025; "RAG", OR = 1.93, p = 0.043; and "RAV", OR = 1.56, p = 0.003) were associated with T1D risk, while two motifs ("REG" and "REV") were equally protective (OR = 0.11, p = 4.23 × 10-4). In an independent birth cohort of HLA-DR3 and HLA-DR4 subjects, those having the "KAG" motif had increased risk for time-to-seroconversion (Hazard Ratio = 1.74, p = 6.51 × 10-14) after adjusting potential confounders. INTERPRETATIONS: DNA sequence variation in HLA-DRB1 at positions ß71, ß74, and ß86 are non-conservative (ß74 A→E, ß71 E vs K vs R and ß86 G vs V). They result in substantial differences in peptide antigen anchor pocket preferences at p1, p4 and potentially neighboring regions such as pocket p7. Differential peptide antigen binding is likely to be affected. These sequence substitutions may account for most of the HLA-DR4 contribution to T1D risk as illustrated in two HLA-peptide model complexes of the T1D autoantigens preproinsulin and GAD65. FUNDING: National Institute of Diabetes and Digestive and Kidney Diseases and the Swedish Child Diabetes Foundation and the Swedish Research Council.

Next-Generation HLA Sequence Analysis Uncovers Seven HLA-DQ Amino Acid Residues and Six Motifs Resistant to Childhood Type 1 Diabetes.

HLA-DQA1 and -DQB1 genes have significant and potentially causal associations with autoimmune type 1 diabetes (T1D). To follow up on the earlier analysis on high-risk HLA-DQ2.5 and DQ8.1, the current analysis uncovers seven residues (αa1, α157, α196, ß9, ß30, ß57, and ß70) that are resistant to T1D among subjects with DQ4-, 5-, 6-, and 7-resistant DQ haplotypes. These 7 residues form 13 common motifs: 6 motifs are significantly resistant, 6 motifs have modest or no associations (P values >0.05), and 1 motif has 7 copies observed among control subjects only. The motifs "DAAFYDG," "DAAYHDG," and "DAAYYDR" have significant resistance to T1D (odds ratios [ORs] 0.03, 0.25, and 0.18; P = 6.11 × 10-24, 3.54 × 10-15, and 1.03 × 10-21, respectively). Remarkably, a change of a single residue from the motif "DAAYHDG" to "DAAYHSG" (D to S at ß57) alters the resistance potential, from resistant motif (OR 0.15; P = 3.54 × 10-15) to a neutral motif (P = 0.183), the change of which was significant (Fisher P value = 0.0065). The extended set of linked residues associated with T1D resistance and unique to each cluster of HLA-DQ haplotypes represents facets of all known features and functions of these molecules: antigenic peptide binding, peptide-MHC class II complex stability, ß167-169 RGD loop, T-cell receptor binding, formation of homodimer of α-ß heterodimers, and cholesterol binding in the cell membrane rafts. Identification of these residues is a novel understanding of resistant DQ associations with T1D. Our analyses endow potential molecular approaches to identify immunological mechanisms that control disease susceptibility or resistance to provide novel targets for immunotherapeutic strategies.

Motifs of Three HLA-DQ Amino Acid Residues (α44, ß57, ß135) Capture Full Association With the Risk of Type 1 Diabetes in DQ2 and DQ8 Children.

HLA-DQA1 and -DQB1 are strongly associated with type 1 diabetes (T1D), and DQ8.1 and DQ2.5 are major risk haplotypes. Next-generation targeted sequencing of HLA-DQA1 and -DQB1 in Swedish newly diagnosed 1- to 18 year-old patients (n = 962) and control subjects (n = 636) was used to construct abbreviated DQ haplotypes, converted into amino acid (AA) residues, and assessed for their associations with T1D. A hierarchically organized haplotype (HOH) association analysis allowed 45 unique DQ haplotypes to be categorized into seven clusters. The DQ8/9 cluster included two DQ8.1 risk and the DQ9 resistant haplotypes, and the DQ2 cluster included the DQ2.5 risk and DQ2.2 resistant haplotypes. Within each cluster, HOH found residues α44Q (odds ratio [OR] 3.29, P = 2.38 * 10-85) and ß57A (OR 3.44, P = 3.80 * 10-84) to be associated with T1D in the DQ8/9 cluster representing all ten residues (α22, α23, α44, α49, α51, α53, α54, α73, α184, ß57) due to complete linkage disequilibrium (LD) of α44 with eight such residues. Within the DQ2 cluster and due to LD, HOH analysis found α44C and ß135D to share the risk for T1D (OR 2.10, P = 1.96 * 10-20). The motif "QAD" of α44, ß57, and ß135 captured the T1D risk association of DQ8.1 (OR 3.44, P = 3.80 * 10-84), and the corresponding motif "CAD" captured the risk association of DQ2.5 (OR 2.10, P = 1.96 * 10-20). Two risk associations were related to GAD65 autoantibody (GADA) and IA-2 autoantibody (IA-2A) but in opposite directions. CAD was positively associated with GADA (OR 1.56, P = 6.35 * 10-8) but negatively with IA-2A (OR 0.59, P = 6.55 * 10-11). QAD was negatively associated with GADA (OR 0.88; P = 3.70 * 10-3) but positively with IA-2A (OR 1.64; P = 2.40 * 10-14), despite a single difference at α44. The residues are found in and around anchor pockets 1 and 9, as potential T-cell receptor contacts, in the areas for CD4 binding and putative homodimer formation. The identification of three HLA-DQ AAs (α44, ß57, ß135) conferring T1D risk should sharpen functional and translational studies.

Comparison of sequence-specific oligonucleotide probe vs next generation sequencing for HLA-A, B, C, DRB1, DRB3/B4/B5, DQA1, DQB1, DPA1, and DPB1 typing: Toward single-pass high-resolution HLA typing in support of solid organ and hematopoietic cell transplant programs.

Many clinical laboratories supporting solid organ transplant programs use multiple HLA genotyping technologies, depending on individual laboratory needs. Sequence-specific primers and quantitative polymerase chain reaction (qPCR) serve the rapid turnaround necessary for deceased donor workup, while sequence-specific oligonucleotide probe (SSOP) technology is widely employed for higher volumes. When clinical need mandates high-resolution data, Sanger sequencing-based typing (SBT) has been the "gold standard." However, all those methods commonly yield ambiguous typing results that utilize valuable laboratory resources when resolution is required. In solid organ transplantation, high-resolution typing may provide critical information for highly sensitized patients with donor-specific anti-HLA antibodies (DSA), particularly when DSA involve HLA alleles not discriminated by SSOP typing. Arguments against routine use of SBT include assay complexity, long turnaround times (TAT), and increased costs. Here, we compare a next generation sequencing (NGS) technology with SSOP for accuracy, effort, turnaround time, and level of resolution for genotyping of 11 HLA loci among 289 specimens from five clinical laboratories. Results were concordant except for SSOP misassignments in eight specimens and 21 novel sequences uniquely identified by NGS. With few exceptions, SSOP generated ambiguous results while NGS provided unambiguous three-field allele assignments. For complete HLA genotyping of up to 24 samples by either SSOP or NGS, bench work was completed on day 1 and typing results were available on day 2. This study provides compelling evidence that, although not viable for STAT typing of deceased donors, a single-pass NGS HLA typing method has direct application for solid organ transplantation.

Eleven Amino Acids of HLA-DRB1 and Fifteen Amino Acids of HLA-DRB3, 4, and 5 Include Potentially Causal Residues Responsible for the Risk of Childhood Type 1 Diabetes.

Next-generation targeted sequencing of HLA-DRB1 and HLA-DRB3, -DRB4, and -DRB5 (abbreviated as DRB345) provides high resolution of functional variant positions to investigate their associations with type 1 diabetes risk and with autoantibodies against insulin (IAA), GAD65 (GADA), IA-2 (IA-2A), and ZnT8 (ZnT8A). To overcome exceptional DR sequence complexity as a result of high polymorphisms and extended linkage disequilibrium among the DR loci, we applied a novel recursive organizer (ROR) to discover disease-associated amino acid residues. ROR distills disease-associated DR sequences and identifies 11 residues of DRB1, sequences of which retain all significant associations observed by DR genes. Furthermore, all 11 residues locate under/adjoining the peptide-binding groove of DRB1, suggesting a plausible functional mechanism through peptide binding. The 15 residues of DRB345, located respectively in the ß49-55 homodimerization patch and on the face of the molecule shown to interact with and bind to the accessory molecule CD4, retain their significant disease associations. Further ROR analysis of DR associations with autoantibodies finds that DRB1 residues significantly associated with ZnT8A and DRB345 residues with GADA. The strongest association is between four residues (ß14, ß25, ß71, and ß73) and IA-2A, in which the sequence ERKA confers a risk association (odds ratio 2.15, P = 10-18), and another sequence, ERKG, confers a protective association (odds ratio 0.59, P = 10-11), despite a difference of only one amino acid. Because motifs of identified residues capture potentially causal DR associations with type 1 diabetes, this list of residuals is expected to include corresponding causal residues in this study population.

Building and validating a prediction model for paediatric type 1 diabetes risk using next generation targeted sequencing of class II HLA genes.

AIM: It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high-risk subjects into longitudinal studies of effective prevention strategies. METHODS: Utilizing a case-control study in Sweden, we applied a recently developed next generation targeted sequencing technology to genotype class II genes and applied an object-oriented regression to build and validate a prediction model for T1D. RESULTS: In the training set, estimated risk scores were significantly different between patients and controls (P = 8.12 × 10-92 ), and the area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was 0.917. Using the validation data set, we validated the result with AUC of 0.886. Combining both training and validation data resulted in a predictive model with AUC of 0.903. Further, we performed a "biological validation" by correlating risk scores with 6 islet autoantibodies, and found that the risk score was significantly correlated with IA-2A (Z-score = 3.628, P < 0.001). When applying this prediction model to the Swedish population, where the lifetime T1D risk ranges from 0.5% to 2%, we anticipate identifying approximately 20 000 high-risk subjects after testing all newborns, and this calculation would identify approximately 80% of all patients expected to develop T1D in their lifetime. CONCLUSION: Through both empirical and biological validation, we have established a prediction model for estimating lifetime T1D risk, using class II HLA. This prediction model should prove useful for future investigations to identify high-risk subjects for prevention research in high-risk populations.

Next-Generation Sequencing Reveals That HLA-DRB3, -DRB4, and -DRB5 May Be Associated With Islet Autoantibodies and Risk for Childhood Type 1 Diabetes.

The possible contribution of HLA-DRB3, -DRB4, and -DRB5 alleles to type 1 diabetes risk and to insulin autoantibody (IAA), GAD65 (GAD autoantibody [GADA]), IA-2 antigen (IA-2A), or ZnT8 against either of the three amino acid variants R, W, or Q at position 325 (ZnT8RA, ZnT8WA, and ZnT8QA, respectively) at clinical diagnosis is unclear. Next-generation sequencing (NGS) was used to determine all DRB alleles in consecutively diagnosed patients ages 1-18 years with islet autoantibody-positive type 1 diabetes (n = 970) and control subjects (n = 448). DRB3, DRB4, or DRB5 alleles were tested for an association with the risk of DRB1 for autoantibodies, type 1 diabetes, or both. The association between type 1 diabetes and DRB1*03:01:01 was affected by DRB3*01:01:02 and DRB3*02:02:01. These DRB3 alleles were associated positively with GADA but negatively with ZnT8WA, IA-2A, and IAA. The negative association between type 1 diabetes and DRB1*13:01:01 was affected by DRB3*01:01:02 to increase the risk and by DRB3*02:02:01 to maintain a negative association. DRB4*01:03:01 was strongly associated with type 1 diabetes (P = 10(-36)), yet its association was extensively affected by DRB1 alleles from protective (DRB1*04:03:01) to high (DRB1*04:01:01) risk, but its association with DRB1*04:05:01 decreased the risk. HLA-DRB3, -DRB4, and -DRB5 affect type 1 diabetes risk and islet autoantibodies. HLA typing with NGS should prove useful to select participants for prevention or intervention trials.

Simultaneous and selective isolation of multiple subpopulations of rare cells from peripheral blood using ensemble-decision aliquot ranking (eDAR).

Rare cells, such as circulating tumor cells (CTCs), can be heterogeneous. The isolation and identification of rare cells with different phenotypes is desirable, for clinical and biological applications. However, CTCs exist in a complex biological environment, which complicates the isolation and identification of particular subtypes. To address this need, we re-designed our ensemble-decision aliquot ranking (eDAR) system to detect, isolate, and study two subpopulations of rare cells in the same microchip. With this dual-capture eDAR device, we simultaneously and selectively isolated two subsets of CTCs from the same blood sample: One set expressed epithelial markers and the other had mesenchymal characteristics. We could apply other selection schemes with different sorting logics to isolate the two subpopulations on demand. The average recovery rate for each subpopulation was higher than 88% with a nearly 100% selectivity of the targeted cells; the throughput was 50 µL min(-1).

An integrated genotyping approach for HLA and other complex genetic systems.

Clinical immunogenetics laboratories performing routine sequencing of human leukocyte antigen (HLA) genes in support of hematopoietic cell transplantation are motivated to upgrade to next-generation sequencing (NGS) technology by its potential for cost savings as well as testing accuracy and flexibility. While NGS machines are available and simple to operate, there are few systems available that provide comprehensive sample preparation and data analysis workflows to complete the process. We report on the development and testing of the Integrated Genotyping System (IGS), which has been designed to specifically address the challenges associated with the adoption of NGS in clinical laboratories. To validate the system for a variety of sample DNA sources, we have tested 336 DNA specimens from whole blood, dried blood spots, buccal swabs, and lymphoblastoid cell lines. HLA class I and class II genotypes were derived from amplicon sequencing of HLA-A, -B, -C for exons 1-7 and HLA-DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4, -DRB5 for exons 1-4. Additionally, to demonstrate the extensibility of the IGS to other genetic loci, KIR haplotyping of 93 samples was carried out in parallel with HLA typing using a workflow based on the HLA system. These results are discussed with respect to their applications in the clinical setting and consequent potential for advancing precision medicine.

New generation of ensemble-decision aliquot ranking based on simplified microfluidic components for large-capacity trapping of circulating tumor cells.

Ensemble-decision aliquot ranking (eDAR) is a sensitive and high-throughput method to analyze circulating tumor cells (CTCs) from peripheral blood. Here, we report the next generation of eDAR, where we designed and optimized a new hydrodynamic switching scheme for the active sorting step in eDAR, which provided fast cell sorting with an improved reproducibility and stability. The microfluidic chip was also simplified by incorporating a functional area for subsequent purification using microslits fabricated by standard lithography method. Using the reported second generation of eDAR, we were able to analyze 1 mL of whole-blood samples in 12.5 min, with a 95% recovery and a zero false positive rate (n = 15).

Dynamic contact angles and hysteresis under electrowetting-on-dielectric.

By designing and implementing a new experimental method, we have measured the dynamic advancing and receding contact angles and the resulting hysteresis of droplets under electrowetting-on-dielectric (EWOD). Measurements were obtained over wide ranges of applied EWOD voltages, or electrowetting numbers (0 ≤ Ew ≤ 0.9), and droplet sliding speeds, or capillary numbers (1.4 × 10(-5) ≤ Ca ≤ 6.9 × 10(-3)). If Ew or Ca is low, dynamic contact angle hysteresis is not affected much by the EWOD voltage or the sliding speed; that is, the hysteresis increases by less than 50% with a 2 order-of-magnitude increase in sliding speed when Ca < 10(-3). If both Ew and Ca are high, however, the hysteresis increases with either the EWOD voltage or the sliding speed. Stick-slip oscillations were observed at Ew > 0.4. Data are interpreted with simplified hydrodynamic (Cox-Voinov) and molecular-kinetic theory (MKT) models; the Cox-Voinov model captures the trend of the data, but it yields unreasonable fitting parameters. MKT fitting parameters associated with the advancing contact line are reasonable, but a lack of symmetry indicates that a more intricate model is required.

A miniature capillary breakup extensional rheometer by electrostatically assisted generation of liquid filaments.

A micromachined chip capable of generating liquid microfilaments has been developed for a miniature version of the Capillary Breakup Extensional Rheometer (CaBER®). The proposed system is exceptionally simple and compact because liquid samples are actuated by voltages administered on-chip, which therefore requires only electrical connections (rather than a linear motor, an integral part of the CaBER®). Since chip features are photolithographically defined, the miniature rheometer can handle sub-microlitre samples. Following the CaBER®, we show that a commercial LED micrometer effectively measures diameters of filaments generated by the electrowetting-on-dielectric (EWOD) forces. Since negligible electric fields are sustained within the liquid far away from the measurement region, the applied EWOD voltage does not influence tested material properties. Through breakup experiments using a wide range of Newtonian and complex fluids (e.g., glycerol, xanthan gum, dilute polystyrene, and dilute solutions of various molecular weight polyethylene oxide) we demonstrate a versatile testing platform for scarce and precious samples such as biochemical fluids and novel materials. Measured Newtonian and complex dynamics agree well with published theories and experiments.

Incubated protein reduction and digestion on an electrowetting-on-dielectric digital microfluidic chip for MALDI-MS.

Localized heating of droplets on an electrowetting-on-dielectric (EWOD) chip has been implemented and shown to accelerate trypsin digestion reaction rates, sample drying, and matrix crystallization for matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). Achieving this involved extending the functionality of previous EWOD droplet-based techniques by developing a multifunctional electrode with closed-loop temperature control, while minimizing overall system complexity and addressing challenges associated with rapid evaporation. For the EWOD chip design, we discuss the performance of multifunctional surface electrodes for actuation, localized Joule heating, and thermistic temperature sensing. Furthermore, a hydrophilic pattern is formed in the multifunctional electrode to control the location of an evaporating droplet on the electrode. To demonstrate the capabilities and limitations of this technique, we performed three experiments and measured the results using MALDI-MS: (i) insulin disulfide reductions in dithiothreitol (DTT) over a range of heater temperatures (22-70 °C) to show how reaction rates can be affected by thermal control, (ii) insulin disulfide reductions at 130 °C in dimethyl sulfoxide (DMSO) to demonstrate a reaction in a high boiling point solvent, and (iii) tryptic digestions of cytochrome c at 22 and 40 °C to show that heated droplets can yield reasonably higher peptide sequence coverage than unheated droplets. Although they do not decouple the effects of changing temperatures and concentrations, these experiments verified that thermal cycling by EWOD electrodes accelerates reaction rates in liquid droplets in air.

Zeta potential and electroosmotic mobility in microfluidic devices fabricated from hydrophobic polymers: 1. The origins of charge.

This paper combines new experimental data for electrokinetic characterization of hydrophobic polymers with a detailed discussion of the putative origins of charge at water-hydrophobe interfaces. Complexities in determining the origin of charge are discussed in the context of design and modeling challenges for electrokinetic actuation in hydrophobic microfluidic devices with aqueous working fluids. Measurements of interfacial charge are complicated by slip and interfacial water structuring phenomena (see Part 2, this issue). Despite these complexities, it is shown that (i) several hydrophobic materials, such as Teflon and Zeonor, have predictable electrokinetic properties and (ii) electrokinetic data for hydrophobic microfluidic systems is most consistent with the postulate that hydroxyl ion adsorption is the origin of charge.