'Gel-Stacks' gently confine or reversibly immobilize arrays of single DNA molecules for manipulation and study.

Large DNA molecules (>20 kb) are difficult analytes prone to breakage during serial manipulations and cannot be 'rescued' as full-length amplicons. Accordingly, to present, modify and analyze arrays of large, single DNA molecules, we created an easily realizable approach offering gentle confinement conditions or immobilization via spermidine condensation for controlled delivery of reagents that support live imaging by epifluorescence microscopy termed 'Gel-Stacks.' Molecules are locally confined between two hydrogel surfaces without covalent tethering to support time-lapse imaging and multistep workflows that accommodate large DNA molecules. With a thin polyacrylamide gel layer covalently bound to a glass surface as the base and swappable, reagent-infused, agarose slabs on top, DNA molecules are stably presented for imaging during reagent delivery by passive diffusion.

A database of restriction maps to expand the utility of bacterial artificial chromosomes.

While Bacterial Artificial Chromosomes libraries were once a key resource for the genomic community, they have been obviated, for sequencing purposes, by long-read technologies. Such libraries may now serve as a valuable resource for manipulating and assembling large genomic constructs. To enhance accessibility and comparison, we have developed a BAC restriction map database. Using information from the National Center for Biotechnology Information's cloneDB FTP site, we constructed a database containing the restriction maps for both uniquely placed and insert-sequenced BACs from 11 libraries covering the recognition sequences of the available restriction enzymes. Along with the database, we generated a set of Python functions to reconstruct the database and more easily access the information within. This data is valuable for researchers simply using BACs, as well as those working with larger sections of the genome in terms of synthetic genes, large-scale editing, and mapping.

Non-linear classification of heart rate parameters as a biomarker for epileptogenesis.

PURPOSE: To characterize a biomarker for epileptogenesis based on cardiac interbeat interval characteristics. METHODS: Electrocardiograph (ECG) and electroencephalogram (EEG) signals were recorded from freely moving rats (n = 23) before status epilepticus (SE) induced by i.p. pilocarpine (PILO) injection as baseline, and on days 1, 3 and 7 after SE. We assessed several features from cardiac interbeat intervals, including linear, non-linear and frequency parameters of interbeat intervals, and power spectra of interpolated intervals during epileptogenesis. After thresholding, the altered values were applied to a non-linear classifier. The non-linear classifier divided animals into two groups; with and without epilepsy, based on all collected data. RESULTS: We found that none of the single altered parameters in cardiac activity emerged as a sole biomarker for epileptogenesis. However, the non-linear classifier distinguished animals that later developed from those and did not develop epilepsy. The non-linear classification was performed on preliminary findings from 23 animals; six did not develop epilepsy and the rest did. The average positive predictive value (precision rate) was 78%. This was calculated based on the average sensitivity and specificity, which were 80.6% and 35.2% respectively, for the 100 classification passes. We also showed that these numbers would have increased as the number of subjects increased. CONCLUSION: Changes to the brain caused by status epilepticus that lead to epileptogenesis have systemic effects, and alter cardiac activity. A non-linear classifier performed on several extracted features of cardiac interbeat intervals may be useful as a biomarker to identify animals with low and high probability of developing epilepsy after status epilepticus.