Biomedical subjects

Emily D Crawford

Publications and source records attributed to Emily D Crawford.

4 recordsLinked to original sources

PubMed2023

FLASH-TB: an Application of Next-Generation CRISPR to Detect Drug Resistant Tuberculosis from Direct Sputum.

Offering patients with tuberculosis (TB) an optimal and timely treatment regimen depends on the rapid detection of Mycobacterium tuberculosis (Mtb) drug resistance from clinical samples. Finding Low Abundance Sequences by Hybridization (FLASH) is a technique that harnesses the efficiency, specificity, and flexibility of the Cas9 enzyme to enrich targeted sequences. Here, we used FLASH to amplify 52 candidate genes probably associated with resistance to first- and second-line drugs in the Mtb reference strain (H37Rv), then detect drug resistance mutations in cultured Mtb isolates, and in sputum samples. 92% of H37Rv reads mapped to Mtb targets, with 97.8% of target regions covered at a depth ≥ 10X. Among cultured isolates, FLASH-TB detected the same 17 drug resistance mutations as whole genome sequencing (WGS) did, but with much greater depth. Among the 16 sputum samples, FLASH-TB increased recovery of Mtb DNA compared with WGS (from 1.4% [IQR 0.5-7.5] to 33% [IQR 4.6-66.3]) and average depth reads of targets (from 6.3 [IQR 3.8-10.5] to 1991 [IQR 254.4-3623.7]). FLASH-TB identified Mtb complex in all 16 samples based on IS1081 and IS6110 copies. Drug resistance predictions for 15/16 (93.7%) clinical samples were highly concordant with phenotypic DST for isoniazid, rifampicin, amikacin, and kanamycin [15/15 (100%)], ethambutol [12/15 (80%)] and moxifloxacin [14/15 (93.3%)]. These results highlighted the potential of FLASH-TB for detecting Mtb drug resistance from sputum samples.

Humans↗

PubMed2006

The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease.

To pursue a systematic approach to the discovery of functional connections among diseases, genetic perturbation, and drug action, we have created the first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules, together with pattern-matching software to mine these data. We demonstrate that this "Connectivity Map" resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs. These results indicate the feasibility of the approach and suggest the value of a large-scale community Connectivity Map project.

Alzheimer Disease↗

PubMed2006

A method for high-throughput gene expression signature analysis.

Genome-wide transcriptional profiling has shown that different biologic states (for instance, disease and response to pharmacologic manipulation) can be recognized by the expression pattern of relatively small numbers of genes. However, the lack of a practical and cost-effective technology for detection of these gene expression 'signatures' in large numbers of samples has severely limited their exploitation in important medical and pharmaceutical discovery applications. Here, we describe a solution based on the combination of ligation-mediated amplification with an optically addressed microsphere and flow cytometric detection system.

Base Sequence↗

PubMed2005

Toward the development of peptide nanofilaments and nanoropes as smart materials.

Protein design studies using coiled coils have illustrated the potential of engineering simple peptides to self-associate into polymers and networks. Although basic aspects of self-assembly in protein systems have been demonstrated, it remains a major challenge to create materials whose large-scale structures are well determined from design of local protein-protein interactions. Here, we show the design and characterization of a helical peptide, which uses phased hydrophobic interactions to drive assembly into nanofilaments and fibrils ("nanoropes"). Using the hydrophobic effect to drive self-assembly circumvents problems of uncontrolled self-assembly seen in previous approaches that used electrostatics as a mode for self-assembly. The nanostructures designed here are characterized by biophysical methods including analytical ultracentrifugation, dynamic light scattering, and circular dichroism to measure their solution properties, and atomic force microscopy to study their behavior on surfaces. Additionally, the assembly of such structures can be predictably regulated by using various environmental factors, such as pH, salt, other molecular crowding reagents, and specifically designed "capping" peptides. This ability to regulate self-assembly is a critical feature in creating smart peptide biomaterials.

Amino Acid Sequence↗