RESUMEN
A major challenge in many clinical diagnostic applications is the measurement of low-abundance proteins and other biomolecules in biological fluids. Digital technologies such as the digital enzyme-linked immunosorbent assay (ELISA) have enabled 1000-fold increases in sensitivity over conventional protein detection methods. However, current digital ELISA technologies still possess insufficient sensitivities for many rare protein biomarkers and require specialized instrumentation or time-consuming workflows that have limited their widespread implementation. To address these challenges, we have developed a more sensitive and streamlined digital ELISA platform, Molecular On-bead Signal Amplification for Individual Counting (MOSAIC), which attains low attomolar limits of detection, with an order of magnitude enhancement in sensitivity over these other methods. MOSAIC uses a rapid, automatable flow cytometric readout that vastly increases throughput and is easily integrated into existing laboratory infrastructure. As MOSAIC provides high sampling efficiencies for rare target molecules, assay bead number can readily be tuned to enhance signal-to-background with high measurement precision. Furthermore, the solution-based signal readout of MOSAIC expands the number of analytes that can simultaneously be measured for higher-order multiplexing with femtomolar sensitivities or below, compared with microwell- or droplet-based digital methods. As a proof of principle, we apply MOSAIC toward improving the detectability of low-abundance cytokines in saliva and ultrasensitive multiplexed measurements of eight protein analytes in plasma and saliva. The attomolar sensitivity, high throughput, and broad multiplexing abilities of MOSAIC provide highly accessible and versatile ultrasensitive capabilities that can potentially accelerate protein biomarker discovery and diagnostic testing for diverse disease applications.
Asunto(s)
Citocinas , Ensayo de Inmunoadsorción Enzimática/métodos , BiomarcadoresRESUMEN
PURPOSE: Clonal hematopoiesis (CH) can be transmitted from a donor to a recipient during allogeneic hematopoietic cell transplantation. Exclusion of candidate donors with CH is controversial since its impact on recipient outcomes and graft alloimmune function is uncertain. PATIENTS AND METHODS: We performed targeted error-corrected sequencing on samples from 1,727 donors age 40 years or older and assessed the effect of donor CH on recipient clinical outcomes. We measured long-term engraftment of 102 donor clones and cytokine levels in 256 recipients at 3 and 12 months after transplant. RESULTS: CH was present in 22.5% of donors, with DNMT3A (14.6%) and TET2 (5.2%) mutations being most common; 85% of donor clones showed long-term engraftment in recipients after transplantation, including clones with a variant allele fraction < 0.01. DNMT3A-CH with a variant allele fraction ≥ 0.01, but not smaller clones, was associated with improved recipient overall (hazard ratio [HR], 0.79; P = .042) and progression-free survival (HR, 0.72; P = .003) after adjustment for significant clinical variables. In patients who received calcineurin-based graft-versus-host disease prophylaxis, donor DNMT3A-CH was associated with reduced relapse (subdistribution HR, 0.59; P = .014), increased chronic graft-versus-host disease (subdistribution HR, 1.36; P = .042), and higher interleukin-12p70 levels in recipients. No recipient of sole DNMT3A or TET2-CH developed donor cell leukemia (DCL). In seven of eight cases, DCL evolved from donor CH with rare TP53 or splicing factor mutations or from donors carrying germline DDX41 mutations. CONCLUSION: Donor CH is closely associated with clinical outcomes in transplant recipients, with differential impact on graft alloimmune function and potential for leukemic transformation related to mutated gene and somatic clonal abundance. Donor DNMT3A-CH is associated with improved recipient survival because of reduced relapse risk and with an augmented network of inflammatory cytokines in recipients. Risk of DCL in allogeneic hematopoietic cell transplantation is driven by somatic myelodysplastic syndrome-associated mutations or germline predisposition in donors.
Asunto(s)
Hematopoyesis Clonal/genética , ADN Metiltransferasa 3A/genética , Proteínas de Unión al ADN/genética , Dioxigenasas/genética , Neoplasias Hematológicas/terapia , Trasplante de Células Madre Hematopoyéticas , Adolescente , Adulto , Anciano , Alelos , Inhibidores de la Calcineurina/uso terapéutico , Niño , Preescolar , Enfermedad Crónica , Citocinas/sangre , Femenino , Enfermedad Injerto contra Huésped/prevención & control , Trasplante de Células Madre Hematopoyéticas/efectos adversos , Humanos , Lactante , Leucemia/etiología , Masculino , Persona de Mediana Edad , Mutación , Supervivencia sin Progresión , Recurrencia , Tasa de Supervivencia , Factores de Tiempo , Trasplante Homólogo , Donante no Emparentado , Adulto JovenRESUMEN
We describe a new genome alignment-based model for understanding the diversity of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of 4-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified. The model goes beyond alignment-free classifications by producing a full phylogeny similar to those constructed by virologists using qualitative features, while relying only on objective genes. These results bolster the case for mathematical models in microbiology which can characterize organisms using only their genetic material and provide an independent check for phylogenies constructed by humans, considerably faster and more cheaply than less modern approaches.