Imtiaz, H. | Search bioRxiv

bioRxiv2024

Paroxysmal Slow Wave Events as a diagnostic and predictive biomarker for post-traumatic epilepsy

Traumatic brain injury (TBI) is a major global health concern, affecting more than 40 million people annually. While most cases are mild and present with light symptoms, repeated mild injuries can result in delayed brain pathologies, including cognitive decline, neuropsychiatric complications, and post-traumatic epilepsy (PTE). PTE refers to recurring, unprovoked seizures occurring at least one week after TBI. While the link between moderate to severe TBI and PTE is well established, the epileptogenesis after repetitive mild TBI (rmTBI) is seldom studied. Currently, there are no biomarkers to identify those at risk of developing PTE, and its diagnosis is challenging. Here, we used a rat model to study PTE following rmTBI and assessed human EEG data to identify potential biomarkers for PTE. We employed a closed head TBI model to induce rmTBI, and recorded brain activity using electrocorticography (ECoG) between 2- and 6-months post-injury. Behavioral assessments and post-mortem analysis were also conducted. In humans, we analyzed EEG recordings from the Temple University database to investigate the potential of EEG-derived features for diagnosing PTE. At 6 months post injury, 70% of rmTBI animals developed PTE, compared to 22% in the control group (P=0.01). While neurological assessments following injury did not predict PTE, paroxysmal slow wave events (PSWEs) were found to be a reliable biomarker for PTE prediction. In humans, the percentage time in PSWEs was significantly elevated in PTE patients with epileptiform activity. In conclusion, we suggest PSWEs as a non-invasive, cost-effective biomarker for PTE in rodents and human patients.

neuroscience↗

bioRxiv2024

CARPDM: cost-effective antibiotic resistome profiling of metagenomic samples using targeted enrichment

Better interrogation of antimicrobial resistance requires new approaches to detect the associated genes in metagenomic samples. Targeted enrichment is an ideal method for their sequencing and characterization. However, no open-source, up-to-date hybridization probe set targeting antimicrobial resistance genes exists. Here we describe CARPDM, a probe design software package made to run alongside all future Comprehensive Antibiotic Resistance Database releases. To test its efficacy, we have created and validated two separate probe sets: AllCARD, which enriches all genes encoded in the Comprehensive Antibiotic Resistance Databases protein homolog models (n = 4,661), and clinicalCARD, which focuses on a clinically relevant subset of resistance genes (n = 323). We demonstrate that allCARD increases the number of reads mapping to resistance genes by up to 594-fold. ClinicalCARD performs similarly when clinically relevant genes are present, increasing the number of resistance-gene mapping reads by up to 598-fold. In parallel with this development, we have established a protocol to synthesize any probe set in-house, saving up to 350 dollars per reaction. Together, these probe sets, their associated design program CARPDM, and the protocol for in-house synthesis will democratize metagenomic resistome analyses, allowing researchers access to a cost-effective and efficient means to explore the antibiotic resistome.

genomics↗