Reproducibility of biophysical in silico neuron states and spikes from event-based partial histories.

Biophysically detailed simulations of neuronal activity often rely on solving large systems of differential equations; in some models, these systems have tens of thousands of states per cell. Numerically solving these equations is computationally intensive and requires making assumptions about the initial cell states. Additional realism from incorporating more biological detail is achieved at the cost of increasingly more states, more computational resources, and more modeling assumptions. We show that for both a point and morphologically-detailed cell model, the presence and timing of future action potentials is probabilistically well-characterized by the relative timings of a moderate number of recent events alone. Knowledge of initial conditions or full synaptic input history is not required. While model time constants, etc. impact the specifics, we demonstrate that for both individual spikes and sustained cellular activity, the uncertainty in spike response decreases as the number of known input events increases, to the point of approximate determinism. Further, we show cellular model states are reconstructable from ongoing synaptic events, despite unknown initial conditions. We propose that a strictly event-based modeling framework is capable of representing the complexity of cellular dynamics of the differential-equations models with significantly less per-cell state variables, thus offering a pathway toward utilizing modern data-driven modeling to scale up to larger network models while preserving individual cellular biophysics.

S-plot2: Rapid Visual and Statistical Analysis of Genomic Sequences.

With the daily release of data from whole genome sequencing projects, tools to facilitate comparative studies are hard-pressed to keep pace. Graphical software solutions can readily recognize synteny by measuring similarities between sequences. Nevertheless, regions of dissimilarity can prove to be equally informative; these regions may harbor genes acquired via lateral gene transfer (LGT), signify gene loss or gain, or include coding regions under strong selection. Previously, we developed the software S-plot. This tool employed an alignment-free approach for comparing bacterial genomes and generated a heatmap representing the genomes' similarities and dissimilarities in nucleotide usage. In prior studies, this tool proved valuable in identifying genome rearrangements as well as exogenous sequences acquired via LGT in several bacterial species. Herein, we present the next generation of this tool, S-plot2. Similar to its predecessor, S-plot2 creates an interactive, 2-dimensional heatmap capturing the similarities and dissimilarities in nucleotide usage between genomic sequences (partial or complete). This new version, however, includes additional metrics for analysis, new reporting options, and integrated BLAST query functionality for the user to interrogate regions of interest. Furthermore, S-plot2 can evaluate larger sequences, including whole eukaryotic chromosomes. To illustrate some of the applications of the tool, 2 case studies are presented. The first examines strain-specific variation across the Pseudomonas aeruginosa genome and strain-specific LGT events. In the second case study, corresponding human, chimpanzee, and rhesus macaque autosomes were studied and lineage specific contributions to divergence were estimated. S-plot2 provides a means to both visually and quantitatively compare nucleotide sequences, from microbial genomes to eukaryotic chromosomes. The case studies presented illustrate just 2 potential applications of the tool, highlighting its capability to identify and investigate the variation in molecular divergence rates across sequences. S-plot2 is freely available through https://bitbucket.org/lkalesinskas/splot and is supported on the Linux and MS Windows operating systems.

Draft Genome Sequence of Micrococcus luteus (Schroeter) Cohn (ATCC 12698).

The actinobacterium Micrococcus luteus can be found in a wide variety of habitats. Here, we report the 2,411,958-bp draft genome sequence of the type strain M. leuteus (Schroeter) Cohn (ATCC 12698). Characteristic of this taxa, the genome sequence has a high G+C content, 73.14%.

Draft Genome Sequence of Enterococcus faecalis ATCC BAA-2128.

While a part of the native gut microflora, the Gram-positive bacterium Enterococcus faecalis can lead to serious infections elsewhere in the body. The draft genome of E. faecalis strain ATCC BAA-2128, isolated from piglet feces, was examined. This draft genome consists of 42 contigs, 12 of which exhibit homology to annotated plasmids.

Draft Genome Sequences of Two ATCC Staphylococcus aureus subsp. aureus Strains.

Draft genome sequences for Staphylococcus aureus subsp. aureus Rosenbach ATCC 14458 and ATCC 27217 strains were investigated. The genome sizes were 2,880,761 bp and 2,759,100 bp, respectively. Strain ATCC 14458 was assembled into 39 contigs, including 3 plasmids, and strain ATCC 27217 was assembled into 25 contigs, including 2 plasmids.

Draft Genome Sequence of Staphylococcus epidermidis (Winslow and Winslow) Evans (ATCC 14990).

Here, we report the draft genome sequence for the type strain Staphylococcus epidermidis (Winslow and Winslow) Evans (ATCC 14990). The assembly consisted of 2,457,519 bp with an observed G+C content of 32.04%. Thirty-seven contigs were produced, including two putative plasmids, with a 296.8× coverage and an N50 of 180,848 bp.