Genomic origin, fragmentomics, and transcriptional properties of long cell-free DNA molecules in human plasma.

Recent studies have revealed an unexplored population of long cell-free DNA (cfDNA) molecules in human plasma using long-read sequencing technologies. However, the biological properties of long cfDNA molecules (>500 bp) remain largely unknown. To this end, we have investigated the origins of long cfDNA molecules from different genomic elements. Analysis of plasma cfDNA using long-read sequencing reveals an uneven distribution of long molecules from across the genome. Long cfDNA molecules show overrepresentation in euchromatic regions of the genome, in sharp contrast to short DNA molecules. We observe a stronger relationship between the abundance of long molecules and mRNA gene expression levels, compared with short molecules (Pearson's r = 0.71 vs. -0.14). Moreover, long and short molecules show distinct fragmentation patterns surrounding CpG sites. Leveraging the cleavage preferences surrounding CpG sites, the combined cleavage ratios of long and short molecules can differentiate patients with hepatocellular carcinoma (HCC) from non-HCC subjects (AUC = 0.87). We also investigated knockout mice in which selected nuclease genes had been inactivated in comparison with wild-type mice. The proportion of long molecules originating from transcription start sites are lower in Dffb-deficient mice but higher in Dnase1l3-deficient mice compared with that of wild-type mice. This work thus provides new insights into the biological properties and potential clinical applications of long cfDNA molecules.

Bolometer operating at the threshold for circuit quantum electrodynamics.

Radiation sensors based on the heating effect of absorbed radiation are typically simple to operate and flexible in terms of input frequency, so they are widely used in gas detection1, security2, terahertz imaging3, astrophysical observations4 and medical applications5. Several important applications are currently emerging from quantum technology and especially from electrical circuits that behave quantum mechanically, that is, circuit quantum electrodynamics6. This field has given rise to single-photon microwave detectors7-9 and a quantum computer that is superior to classical supercomputers for certain tasks10. Thermal sensors hold potential for enhancing such devices because they do not add quantum noise and they are smaller, simpler and consume about six orders of magnitude less power than the frequently used travelling-wave parametric amplifiers11. However, despite great progress in the speed12 and noise levels13 of thermal sensors, no bolometer has previously met the threshold for circuit quantum electrodynamics, which lies at a time constant of a few hundred nanoseconds and a simultaneous energy resolution of the order of 10h gigahertz (where h is the Planck constant). Here we experimentally demonstrate a bolometer that operates at this threshold, with a noise-equivalent power of 30 zeptowatts per square-root hertz, comparable to the lowest value reported so far13, at a thermal time constant two orders of magnitude shorter, at 500 nanoseconds. Both of these values are measured directly on the same device, giving an accurate estimation of 30h gigahertz for the calorimetric energy resolution. These improvements stem from the use of a graphene monolayer with extremely low specific heat14 as the active material. The minimum observed time constant of 200 nanoseconds is well below the dephasing times of roughly 100 microseconds reported for superconducting qubits15 and matches the timescales of currently used readout schemes16,17, thus enabling circuit quantum electrodynamics applications for bolometers.

Operation of a silicon quantum processor unit cell above one kelvin.

Quantum computers are expected to outperform conventional computers in several important applications, from molecular simulation to search algorithms, once they can be scaled up to large numbers-typically millions-of quantum bits (qubits)1-3. For most solid-state qubit technologies-for example, those using superconducting circuits or semiconductor spins-scaling poses a considerable challenge because every additional qubit increases the heat generated, whereas the cooling power of dilution refrigerators is severely limited at their operating temperature (less than 100 millikelvin)4-6. Here we demonstrate the operation of a scalable silicon quantum processor unit cell comprising two qubits confined to quantum dots at about 1.5 kelvin. We achieve this by isolating the quantum dots from the electron reservoir, and then initializing and reading the qubits solely via tunnelling of electrons between the two quantum dots7-9. We coherently control the qubits using electrically driven spin resonance10,11 in isotopically enriched silicon12 28Si, attaining single-qubit gate fidelities of 98.6 per cent and a coherence time of 2 microseconds during 'hot' operation, comparable to those of spin qubits in natural silicon at millikelvin temperatures13-16. Furthermore, we show that the unit cell can be operated at magnetic fields as low as 0.1 tesla, corresponding to a qubit control frequency of 3.5 gigahertz, where the qubit energy is well below the thermal energy. The unit cell constitutes the core building block of a full-scale silicon quantum computer and satisfies layout constraints required by error-correction architectures8,17. Our work indicates that a spin-based quantum computer could be operated at increased temperatures in a simple pumped 4He system (which provides cooling power orders of magnitude higher than that of dilution refrigerators), thus potentially enabling the integration of classical control electronics with the qubit array18,19.

Fragmentation landscape of cell-free DNA revealed by deconvolutional analysis of end motifs.

Cell-free DNA (cfDNA) fragmentation is nonrandom, at least partially mediated by various DNA nucleases, forming characteristic cfDNA end motifs. However, there is a paucity of tools for deciphering the relative contributions of cfDNA cleavage patterns related to underlying fragmentation factors. In this study, through non-negative matrix factorization algorithm, we used 256 5' 4-mer end motifs to identify distinct types of cfDNA cleavage patterns, referred to as "founder" end-motif profiles (F-profiles). F-profiles were associated with different DNA nucleases based on whether such patterns were disrupted in nuclease-knockout mouse models. Contributions of individual F-profiles in a cfDNA sample could be determined by deconvolutional analysis. We analyzed 93 murine cfDNA samples of different nuclease-deficient mice and identified six types of F-profiles. F-profiles I, II, and III were linked to deoxyribonuclease 1 like 3 (DNASE1L3), deoxyribonuclease 1 (DNASE1), and DNA fragmentation factor subunit beta (DFFB), respectively. We revealed that 42.9% of plasma cfDNA molecules were attributed to DNASE1L3-mediated fragmentation, whereas 43.4% of urinary cfDNA molecules involved DNASE1-mediated fragmentation. We further demonstrated that the relative contributions of F-profiles were useful to inform pathological states, such as autoimmune disorders and cancer. Among the six F-profiles, the use of F-profile I could inform the human patients with systemic lupus erythematosus. F-profile VI could be used to detect individuals with hepatocellular carcinoma, with an area under the receiver operating characteristic curve of 0.97. F-profile VI was more prominent in patients with nasopharyngeal carcinoma undergoing chemoradiotherapy. We proposed that this profile might be related to oxidative stress.

Fidelity benchmarks for two-qubit gates in silicon.

Universal quantum computation will require qubit technology based on a scalable platform1, together with quantum error correction protocols that place strict limits on the maximum infidelities for one- and two-qubit gate operations2,3. Although various qubit systems have shown high fidelities at the one-qubit level4-10, the only solid-state qubits manufactured using standard lithographic techniques that have demonstrated two-qubit fidelities near the fault-tolerance threshold6 have been in superconductor systems. Silicon-based quantum dot qubits are also amenable to large-scale fabrication and can achieve high single-qubit gate fidelities (exceeding 99.9 per cent) using isotopically enriched silicon11,12. Two-qubit gates have now been demonstrated in a number of systems13-15, but as yet an accurate assessment of their fidelities using Clifford-based randomized benchmarking, which uses sequences of randomly chosen gates to measure the error, has not been achieved. Here, for qubits encoded on the electron spin states of gate-defined quantum dots, we demonstrate Bell state tomography with fidelities ranging from 80 to 89 per cent, and two-qubit randomized benchmarking with an average Clifford gate fidelity of 94.7 per cent and an average controlled-rotation fidelity of 98 per cent. These fidelities are found to be limited by the relatively long gate times used here compared with the decoherence times of the qubits. Silicon qubit designs employing fast gate operations with high Rabi frequencies16,17, together with advanced pulsing techniques18, should therefore enable much higher fidelities in the near future.

Fragmentomics of urinary cell-free DNA in nuclease knockout mouse models.

Urinary cell-free DNA (ucfDNA) is a potential biomarker for bladder cancer detection. However, the biological characteristics of ucfDNA are not well understood. We explored the roles of deoxyribonuclease 1 (DNASE1) and deoxyribonuclease 1-like 3 (DNASE1L3) in the fragmentation of ucfDNA using mouse models. The deletion of Dnase1 in mice (Dnase1-/-) caused aberrations in ucfDNA fragmentation, including a 24-fold increase in DNA concentration, and a 3-fold enrichment of long DNA molecules, with a relative decrease of fragments with thymine ends and reduction of jaggedness (i.e., the presence of single-stranded protruding ends). In contrast, such changes were not observed in mice with Dnase1l3 deletion (Dnase1l3-/-). These results suggested that DNASE1 was an important nuclease contributing to the ucfDNA fragmentation. Western blot analysis revealed that the concentration of DNASE1 protein was higher in urine than DNASE1L3. The native-polyacrylamide gel electrophoresis zymogram showed that DNASE1 activity in urine was higher than that in plasma. Furthermore, the proportion of ucfDNA fragment ends within DNase I hypersensitive sites (DHSs) was significantly increased in Dnase1-deficient mice. In humans, patients with bladder cancer had lower proportions of ucfDNA fragment ends within the DHSs when compared with participants without bladder cancer. The area under the curve (AUC) for differentiating patients with and without bladder cancer was 0.83, suggesting the analysis of ucfDNA fragmentation in the DHSs may have potential for bladder cancer detection. This work revealed the intrinsic links between the nucleases in urine and ucfDNA fragmentomics.

Epigenetic analysis of cell-free DNA by fragmentomic profiling.

Cell-free DNA (cfDNA) fragmentation patterns contain important molecular information linked to tissues of origin. We explored the possibility of using fragmentation patterns to predict cytosine-phosphate-guanine (CpG) methylation of cfDNA, obviating the use of bisulfite treatment and associated risks of DNA degradation. This study investigated the cfDNA cleavage profile surrounding a CpG (i.e., within an 11-nucleotide [nt] window) to analyze cfDNA methylation. The cfDNA cleavage proportion across positions within the window appeared nonrandom and exhibited correlation with methylation status. The mean cleavage proportion was ∼twofold higher at the cytosine of methylated CpGs than unmethylated ones in healthy controls. In contrast, the mean cleavage proportion rapidly decreased at the 1-nt position immediately preceding methylated CpGs. Such differential cleavages resulted in a characteristic change in relative presentations of CGN and NCG motifs at 5' ends, where N represented any nucleotide. CGN/NCG motif ratios were correlated with methylation levels at tissue-specific methylated CpGs (e.g., placenta or liver) (Pearson's absolute r > 0.86). cfDNA cleavage profiles were thus informative for cfDNA methylation and tissue-of-origin analyses. Using CG-containing end motifs, we achieved an area under a receiver operating characteristic curve (AUC) of 0.98 in differentiating patients with and without hepatocellular carcinoma and enhanced the positive predictive value of nasopharyngeal carcinoma screening (from 19.6 to 26.8%). Furthermore, we elucidated the feasibility of using cfDNA cleavage patterns to deduce CpG methylation at single CpG resolution using a deep learning algorithm and achieved an AUC of 0.93. FRAGmentomics-based Methylation Analysis (FRAGMA) presents many possibilities for noninvasive prenatal, cancer, and organ transplantation assessment.

Nuclease deficiencies alter plasma cell-free DNA methylation profiles.

The effects of DNASE1L3 or DNASE1 deficiency on cell-free DNA (cfDNA) methylation were explored in plasma of mice deficient in these nucleases and in DNASE1L3-deficient humans. Compared to wild-type cfDNA, cfDNA in DNASE1L3-deficient mice was significantly hypomethylated, while cfDNA in DNASE1-deficient mice was hypermethylated. The cfDNA hypomethylation in DNASE1L3-deficient mice was due to increased fragmentation and representation from open chromatin regions (OCRs) and CpG islands (CGIs). These findings were absent in DNASE1-deficient mice, demonstrating the preference of DNASE1 to cleave in hypomethylated OCRs and CGIs. We also observed a substantial decrease of fragment ends at methylated CpGs in the absence of DNASE1L3, thereby demonstrating that DNASE1L3 prefers to cleave at methylated CpGs. Furthermore, we found that methylation levels of cfDNA varied by fragment size in a periodic pattern, with cfDNA of specific sizes being more hypomethylated and enriched for OCRs and CGIs. These findings were confirmed in DNASE1L3-deficient human cfDNA. Thus, we have found that nuclease-mediated cfDNA fragmentation markedly affects cfDNA methylation level on a genome-wide scale. This work provides a foundational understanding of the relationship between methylation, nuclease biology, and cfDNA fragmentation.

Universal Targeted Haplotyping by Droplet Digital PCR Sequencing and Its Applications in Noninvasive Prenatal Testing and Pharmacogenetics Analysis.

BACKGROUND: The analysis of haplotypes of variants is important for pharmacogenomics analysis and noninvasive prenatal testing for monogenic diseases. However, there is a lack of robust methods for targeted haplotyping. METHODS: We developed digital PCR haplotype sequencing (dHapSeq) for targeted haplotyping of variants, which is a method that compartmentalizes long DNA molecules into droplets. Within one droplet, 2 target regions are PCR amplified from one template molecule, and their amplicons are fused together. The fused products are then sequenced to determine the phase relationship of the single nucleotide polymorphism (SNP) alleles. The entire haplotype of 10s of SNPs can be deduced after the phase relationship of individual SNPs are determined in a pairwise manner. We applied dHapSeq to noninvasive prenatal testing in 4 families at risk for thalassemia and utilized it to detect NUDT15 diplotypes for predicting drug tolerance in pediatric acute lymphoblastic leukemia (72 cases and 506 controls). RESULTS: For SNPs within 40 kb, phase relation can be determined with 100% accuracy. In 7 trio families, the haplotyping results for 97 SNPs spanning 185 kb determined by dHapSeq were concordant with the results deduced from the genotypes of both parents and the fetus. In 4 thalassemia families, a 19.3-kb Southeast Asian deletion was successfully phased with 97 downstream SNPs, enabling noninvasive determination of fetal inheritance using relative haplotype dosage analysis. In the NUDT15 analysis, the variant status and phase of the variants were successfully determined in all cases and controls. CONCLUSIONS: The dHapSeq represents a robust and scalable haplotyping approach with numerous clinical and research applications.

Uses of antiseizure medication among pregnant women with epilepsy and risk of adverse obstetric outcomes: A group-based trajectory analysis.

OBJECTIVE: This study was undertaken to examine the association between different patterns of antiseizure medication (ASM) use during pregnancy and adverse obstetric outcomes (preterm birth, low birth weight [LBW], and small for gestational age [SGA]). METHODS: This retrospective cohort study used the Birth Certificate Application and National Health Insurance data in Taiwan (January 1, 2004 through December 31, 2018). We retrieved weekly ASM among pregnant women with epilepsy who were prepregnancy chronic users and used group-based trajectory modeling to identify distinct patterns of use. Logistic regressions were adopted to examine the association between patterns of ASM use and risk of preterm birth, LBW, and SGA. In addition, we revealed postnatal ASM utilization pattern among these prepregnancy chronic users as an exploratory study. RESULTS: Of 2175 pregnant women with epilepsy, we identified four patterns of ASM use during pregnancy: frequent and continuous (64.87%), frequent but discontinuous (7.08%), intermittent (19.72%), and intermittent and discontinuous users (8.32%). Compared to frequent and continuous users, the adjusted odds ratios for preterm birth in frequent but discontinuous, intermittent, and intermittent and discontinuous users were .83 (95% confidence interval [CI] = .47-1.48), .71 (95% CI = .47-1.05), and .88 (95% CI = .52-1.49), respectively. Similar results were observed for LBW and SGA. In the exploratory study, we found that most of our study subjects maintained the same patterns before and after delivery. SIGNIFICANCE: After considering duration and timing of exposure, our study did not find an association between four distinct patterns of ASM use and adverse obstetric outcomes among women with epilepsy. The findings suggested that optimal seizure control could be received for pregnant women with epilepsy after evaluating the risks and benefits.

Updated core competencies in pharmacoepidemiology to inform contemporary curricula and training for academia, government, and industry.

PURPOSE: The first paper to specify the core content of pharmacoepidemiology as a profession was published by an ISPE (International Society for Pharmacoepidemiology) workgroup in 2012 (Jones JK et al. PDS 2012; 21[7]:677-689). Due to the broader and evolving scope of pharmacoepidemiology, ISPE considers it important to proactively identify, update and expand the list of core competencies to inform curricula of education programs; thus, better positioning pharmacoepidemiologists across academic, government (including regulatory), and industry positions. The aim of this project was to update the list of core competencies in pharmacoepidemiology. METHODS: To ensure applicability of findings to multiple areas, a working group was established consisting of ISPE members with positions in academia, industry, government, and other settings. All competencies outlined by Jones et al. were extracted from the initial manuscript and presented to the working group for review. Expert-based judgments were collated and used to identify consensus. It was noted that some competencies could contribute to multiple groups and could be directly or indirectly related to a group. RESULTS: Five core domains were proposed: (1) Epidemiology, (2) Clinical Pharmacology, (3) Regulatory Science, (4) Statistics and data science, and (5) Communication and other professional skills. In total, 55 individual competencies were proposed, of which 25 were new competencies. No competencies from the original work were dropped but aggregation or amendments were made where considered necessary. CONCLUSIONS: While many core competencies in pharmacoepidemiology have remained the same over the past 10 years, there have also been several updates to reflect new and emerging concepts in the field.

Risk of serious infection and infection mortality in patients with psoriasis: A nationwide cohort study using the Taiwan National Health Insurance claims database.

BACKGROUND: The risks of serious infections that lead to hospitalization and mortality in patients with psoriasis in Asia have not been comprehensively studied. OBJECTIVES: We examined the incidence of serious infection and infection mortality in patients with psoriasis. METHODS: This population-based retrospective cohort study used the Taiwan National Health Insurance claims database from 2000 to 2017. Adult patients with psoriasis were identified by a relevant International Classification of Diseases (ICD) code and matched to six comparators without psoriasis on age and sex. Psoriasis patients were categorized as having moderate-to-severe disease once exposed to systemic therapies, phototherapy or biologic therapies. The incidence of serious infection and infection mortality were identified by ICD codes from inpatient hospitalization and death registration. Cox proportional hazard models were used to compare the risk, and the results were adjusted for covariates and presented as adjusted hazard ratios (aHR) and 95% confidence interval (95% CI). RESULTS: Overall, 185,434 psoriasis patients and 1,112,581 comparators were included. A higher rate of serious infection (aHR: 1.21, 95% CI: 1.19-1.22) was found in patients with psoriasis compared to matched comparators without psoriasis, and the risk was enhanced when patients had moderate-to-severe psoriasis (aHR: 1.30, 95% CI: 1.27-1.34). Specifically, there was an increased risk of serious infection due to respiratory infections (aHR: 1.11, 95% CI: 1.09-1.13), skin/soft-tissue infections (aHR: 1.57, 95% CI: 1.52-1.62), sepsis (aHR: 1.23, 95% CI: 1.19-1.27), urinary tract infections (aHR: 1.11, 95% CI: 1.08-1.14), hepatitis B (aHR: 1.18, 95% CI: 1.06-1.30) and hepatitis C (aHR: 1.49, 95% CI: 1.32-1.69). Furthermore, psoriasis patients were associated with a higher risk of infection-related mortality (aHR: 1.15, 95% CI: 1.11-1.18) compared to matched comparators. CONCLUSION: Patients with psoriasis had a higher risk of serious infection and infection mortality, which was enhanced by moderate-to-severe psoriasis. Practitioners should be aware of the increased risk in patients with psoriasis, but it should not be a barrier to offering effective treatment.

Genome-wide detection of cytosine methylation by single molecule real-time sequencing.

5-Methylcytosine (5mC) is an important type of epigenetic modification. Bisulfite sequencing (BS-seq) has limitations, such as severe DNA degradation. Using single molecule real-time sequencing, we developed a methodology to directly examine 5mC. This approach holistically examined kinetic signals of a DNA polymerase (including interpulse duration and pulse width) and sequence context for every nucleotide within a measurement window, termed the holistic kinetic (HK) model. The measurement window of each analyzed double-stranded DNA molecule comprised 21 nucleotides with a cytosine in a CpG site in the center. We used amplified DNA (unmethylated) and M.SssI-treated DNA (methylated) (M.SssI being a CpG methyltransferase) to train a convolutional neural network. The area under the curve for differentiating methylation states using such samples was up to 0.97. The sensitivity and specificity for genome-wide 5mC detection at single-base resolution reached 90% and 94%, respectively. The HK model was then tested on human-mouse hybrid fragments in which each member of the hybrid had a different methylation status. The model was also tested on human genomic DNA molecules extracted from various biological samples, such as buffy coat, placental, and tumoral tissues. The overall methylation levels deduced by the HK model were well correlated with those by BS-seq (r = 0.99; P < 0.0001) and allowed the measurement of allele-specific methylation patterns in imprinted genes. Taken together, this methodology has provided a system for simultaneous genome-wide genetic and epigenetic analyses.

Single-molecule sequencing reveals a large population of long cell-free DNA molecules in maternal plasma.

In the field of circulating cell-free DNA, most of the studies have focused on short DNA molecules (e.g., <500 bp). The existence of long cell-free DNA molecules has been poorly explored. In this study, we demonstrated that single-molecule real-time sequencing allowed us to detect and analyze a substantial proportion of long DNA molecules from both fetal and maternal sources in maternal plasma. Such molecules were beyond the size detection limits of short-read sequencing technologies. The proportions of long cell-free DNA molecules in maternal plasma over 500 bp were 15.5%, 19.8%, and 32.3% for the first, second, and third trimesters, respectively. The longest fetal-derived plasma DNA molecule observed was 23,635 bp. Long plasma DNA molecules demonstrated predominance of A or G 5' fragment ends. Pregnancies with preeclampsia demonstrated a reduction in long maternal plasma DNA molecules, reduced frequencies for selected 5' 4-mer end motifs ending with G or A, and increased frequencies for selected motifs ending with T or C. Finally, we have developed an approach that employs the analysis of methylation patterns of the series of CpG sites on a long DNA molecule for determining its tissue origin. This approach achieved an area under the curve of 0.88 in differentiating between fetal and maternal plasma DNA molecules, enabling the determination of maternal inheritance and recombination events in the fetal genome. This work opens up potential clinical utilities of long cell-free DNA analysis in maternal plasma including noninvasive prenatal testing of monogenic diseases and detection/monitoring of pregnancy-associated disorders such as preeclampsia.

Prediction of hospital mortality among critically ill patients in a single centre in Asia: comparison of artificial neural networks and logistic regression-based model.

INTRODUCTION: This study compared the performance of the artificial neural network (ANN) model with the Acute Physiologic and Chronic Health Evaluation (APACHE) II and IV models for predicting hospital mortality among critically ill patients in Hong Kong. METHODS: This retrospective analysis included all patients admitted to the intensive care unit of Pamela Youde Nethersole Eastern Hospital from January 2010 to December 2019. The ANN model was constructed using parameters identical to the APACHE IV model. Discrimination performance was assessed using area under the receiver operating characteristic curve (AUROC); calibration performance was evaluated using the Brier score and Hosmer-Lemeshow statistic. RESULTS: In total, 14 503 patients were included, with 10% in the validation set and 90% in the ANN model development set. The ANN model (AUROC=0.88, 95% confidence interval [CI]=0.86-0.90, Brier score=0.10; P in Hosmer-Lemeshow test=0.37) outperformed the APACHE II model (AUROC=0.85, 95% CI=0.80-0.85, Brier score=0.14; P<0.001 for both comparisons of AUROCs and Brier scores) but showed performance similar to the APACHE IV model (AUROC=0.87, 95% CI=0.85-0.89, Brier score=0.11; P=0.34 for comparison of AUROCs, and P=0.05 for comparison of Brier scores). The ANN model demonstrated better calibration than the APACHE II and APACHE IV models. CONCLUSION: Our ANN model outperformed the APACHE II model but was similar to the APACHE IV model in terms of predicting hospital mortality in Hong Kong. Artificial neural networks are valuable tools that can enhance real-time prognostic prediction.

Amorphous Thickness-Dependent Strengthening-Softening Transition in Crystalline-Amorphous Nanocomposites.

Core-shell crystalline-amorphous nanocomposites, featuring nanograins surrounded by thick amorphous boundaries, are promising nanoarchitectures for achieving exceptional strength through cooperative strengthening effects. However, a comprehensive understanding of the influence of characteristic sizes, particularly the amorphous thickness, on codeformation strengthening is still lacking, limiting the attainment of the strength limit. Here, we employ molecular dynamics simulations to investigate Cu-CuTa crystalline-amorphous nanocomposites with varying grain sizes and amorphous thicknesses. Our findings demonstrate significant strengthening effects in nanocomposites, effectively suppressing the Hall-Petch breakdown observed in traditional amorphous-free nanograined Cu. Intriguingly, we observe a maximum strength followed by a strengthening-softening transition dependent on the amorphous thickness, as exemplified by a representative nanocomposite featuring a 12.5 nm grain size and a critical amorphous thickness of 4 nm. Inspired by observed shifts in atomistic mechanisms, we developed a theoretical model encompassing variations in grain size and amorphous thickness, providing valuable insights into the size-strength relationship for crystalline-amorphous nanocomposites.

Plasma DNA Profile Associated with DNASE1L3 Gene Mutations: Clinical Observations, Relationships to Nuclease Substrate Preference, and In Vivo Correction.

Plasma DNA fragmentomics is an emerging area in cell-free DNA diagnostics and research. In murine models, it has been shown that the extracellular DNase, DNASE1L3, plays a role in the fragmentation of plasma DNA. In humans, DNASE1L3 deficiency causes familial monogenic systemic lupus erythematosus with childhood onset and anti-dsDNA reactivity. In this study, we found that human patients with DNASE1L3 disease-associated gene variations showed aberrations in size and a reduction of a "CC" end motif of plasma DNA. Furthermore, we demonstrated that DNA from DNASE1L3-digested cell nuclei showed a median length of 153 bp with CC motif frequencies resembling plasma DNA from healthy individuals. Adeno-associated virus-based transduction of Dnase1l3 into Dnase1l3-deficient mice restored the end motif profiles to those seen in the plasma DNA of wild-type mice. Our findings demonstrate that DNASE1L3 is an important player in the fragmentation of plasma DNA, which appears to act in a cell-extrinsic manner to regulate plasma DNA size and motif frequency.

Detection and characterization of jagged ends of double-stranded DNA in plasma.

Cell-free DNA in plasma has been used for noninvasive prenatal testing and cancer liquid biopsy. The physical properties of cell-free DNA fragments in plasma, such as fragment sizes and ends, have attracted much recent interest, leading to the emerging field of cell-free DNA fragmentomics. However, one aspect of plasma DNA fragmentomics as to whether double-stranded plasma molecules might carry single-stranded ends, termed a jagged end in this study, remains underexplored. We have developed two approaches for investigating the presence of jagged ends in a plasma DNA pool. These approaches utilized DNA end repair to introduce differential methylation signals between the original sequence and the jagged ends, depending on whether unmethylated or methylated cytosines were used in the DNA end-repair procedure. The majority of plasma DNA molecules (87.8%) were found to bear jagged ends. The jaggedness varied according to plasma DNA fragment sizes and appeared to be in association with nucleosomal patterns. In the plasma of pregnant women, the jaggedness of fetal DNA molecules was higher than that of the maternal counterparts. The jaggedness of plasma DNA correlated with the fetal DNA fraction. Similarly, in the plasma of cancer patients, tumor-derived DNA molecules in patients with hepatocellular carcinoma showed an elevated jaggedness compared with nontumoral DNA. In mouse models, knocking out of the Dnase1 gene reduced jaggedness, whereas knocking out of the Dnase1l3 gene enhanced jaggedness. Hence, plasma DNA jagged ends represent an intrinsic property of plasma DNA and provide a link between nuclease activities and the fragmentation of plasma DNA.

Fragment Ends of Circulating Microbial DNA as Signatures for Pathogen Detection in Sepsis.

BACKGROUND: Nuclear-derived cell-free DNA (cfDNA) molecules in blood plasma are nonrandomly fragmented, bearing a wealth of information related to tissues of origin. DNASE1L3 (deoxyribonuclease 1 like 3) is an important player in shaping the fragmentation of nuclear-derived cfDNA molecules, preferentially generating molecules with 5 CC dinucleotide termini (i.e., 5 CC-end motif). However, the fragment end properties of microbial cfDNA and its clinical implication remain to be explored. METHODS: We performed end motif analysis on microbial cfDNA fragments in plasma samples from patients with sepsis. A sequence context-based normalization method was used to minimize the potential biases for end motif analysis. RESULTS: The end motif profiles of microbial cfDNA appeared to resemble that of nuclear cfDNA (Spearman correlation coefficient: 0.82, P value 0.001). The CC-end motif was the most preferred end motif in microbial cfDNA, suggesting that DNASE1L3 might also play a role in the fragmentation of microbe-derived cfDNA in plasma. Of note, differential end motifs were present between microbial cfDNA originating from infection-causing pathogens (enriched at the CC-end) and contaminating microbial DNA potentially derived from reagents or the environment (nearly random). The use of fragment end signatures allowed differentiation between confirmed pathogens and contaminating microbes, with an area under the receiver operating characteristic curve of 0.99. The performance appeared to be superior to conventional analysis based on microbial cfDNA abundance alone. CONCLUSIONS: The use of fragmentomic features could facilitate the differentiation of underlying contaminating microbes from true pathogens in sepsis. This work demonstrates the potential usefulness of microbial cfDNA fragmentomics in metagenomics analysis.

Comparison of Single Molecule, Real-Time Sequencing and Nanopore Sequencing for Analysis of the Size, End-Motif, and Tissue-of-Origin of Long Cell-Free DNA in Plasma.

BACKGROUND: Recent studies using single molecule, real-time (SMRT) sequencing revealed a substantial population of analyzable long cell-free DNA (cfDNA) in plasma. Potential clinical utilities of such long cfDNA in pregnancy and cancer have been demonstrated. However, the performance of different long-read sequencing platforms for the analysis of long cfDNA remains unknown. METHODS: Size biases of SMRT sequencing by Pacific Biosciences (PacBio) and nanopore sequencing by Oxford Nanopore Technologies (ONT) were evaluated using artificial mixtures of sonicated human and mouse DNA of different sizes. cfDNA from plasma samples of pregnant women at different trimesters, hepatitis B carriers, and patients with hepatocellular carcinoma were sequenced with the 2 platforms. RESULTS: Both platforms showed biases to sequence longer (1500 bp vs 200 bp) DNA fragments, with PacBio showing a stronger bias (5-fold overrepresentation of long fragments vs 2-fold in ONT). Percentages of cfDNA fragments 500 bp were around 6-fold higher in PacBio compared with ONT. End motif profiles of cfDNA from PacBio and ONT were similar, yet exhibited platform-dependent patterns. Tissue-of-origin analysis based on single-molecule methylation patterns showed comparable performance on both platforms. CONCLUSIONS: SMRT sequencing generated data with higher percentages of long cfDNA compared with nanopore sequencing. Yet, a higher number of long cfDNA fragments eligible for the tissue-of-origin analysis could be obtained from nanopore sequencing due to its much higher throughput. When analyzing the size and end motif of cfDNA, one should be aware of the analytical characteristics and possible biases of the sequencing platforms being used.