CaMKII binds both substrates and activators at the active site.

Ca2+/calmodulin-dependent protein kinase II (CaMKII) is a signaling protein required for long-term memory. When activated by Ca2+/CaM, it sustains activity even after the Ca2+ dissipates. In addition to the well-known autophosphorylation-mediated mechanism, interaction with specific binding partners also persistently activates CaMKII. A long-standing model invokes two distinct S and T sites. If an interactor binds at the T-site, then it will preclude autoinhibition and allow substrates to be phosphorylated at the S site. Here, we specifically test this model with X-ray crystallography, molecular dynamics simulations, and biochemistry. Our data are inconsistent with this model. Co-crystal structures of four different activators or substrates show that they all bind to a single continuous site across the kinase domain. We propose a mechanistic model where persistent CaMKII activity is facilitated by high-affinity binding partners that kinetically compete with autoinhibition by the regulatory segment to allow substrate phosphorylation.

Functional implications of CaMKII alternative splicing.

Ca2+ /calmodulin-dependent protein kinase II (CaMKII) is known to be a crucial regulator in the post-synapse during long-term potentiation. This important protein has been the subject of many studies centered on understanding memory at the molecular, cellular, and organismic level. CaMKII is encoded by four genes in humans, all of which undergo alternative splicing at the RNA level, leading to an enormous diversity of expressed proteins. Advances in sequencing technologies have facilitated the discovery of many new CaMKII transcripts. To date, newly discovered CaMKII transcripts have been incorporated into an ambiguous naming scheme. Herein, we review the initial experiments leading to the discovery of CaMKII and its subsequent variants. We propose the adoption of a new, unambiguous naming scheme for CaMKII variants. Finally, we discuss biological implications for CaMKII splice variants.

Heterogeneity in human hippocampal CaMKII transcripts reveals allosteric hub-dependent regulation.

Calcium/calmodulin-dependent protein kinase II (CaMKII) plays a central role in Ca2+ signaling throughout the body. In the hippocampus, CaMKII is required for learning and memory. Vertebrate genomes encode four CaMKII homologs: CaMKIIα, CaMKIIß, CaMKIIγ, and CaMKIIδ. All CaMKIIs consist of a kinase domain, a regulatory segment, a variable linker region, and a hub domain, which is responsible for oligomerization. The four proteins differ primarily in linker length and composition because of extensive alternative splicing. Here, we report the heterogeneity of CaMKII transcripts in three complex samples of human hippocampus using deep sequencing. We showed that hippocampal cells contain a diverse collection of over 70 CaMKII transcripts from all four CaMKII-encoding genes. We characterized the Ca2+/CaM sensitivity of hippocampal CaMKII variants spanning a broad range of linker lengths and compositions. The effect of the variable linker on Ca2+/CaM sensitivity depended on the kinase and hub domains. Moreover, we revealed a previously uncharacterized role for the hub domain as an allosteric regulator of kinase activity, which may provide a pharmacological target for modulating CaMKII activity. Using small-angle x-ray scattering and single-particle cryo-electron microscopy (cryo-EM), we present evidence for extensive interactions between the kinase and the hub domains, even in the presence of a 30-residue linker. Together, these data suggest that Ca2+/CaM sensitivity in CaMKII is homolog dependent and includes substantial contributions from the hub domain. Our sequencing approach, combined with biochemistry, provides insights into understanding the complex pool of endogenous CaMKII splice variants.

ASPEN, a methodology for reconstructing protein evolution with improved accuracy using ensemble models.

Evolutionary reconstruction algorithms produce models of the evolutionary history of proteins or species. Such algorithms are highly sensitive to their inputs: the sequences used and their alignments. Here, we asked whether the variance introduced by selecting different input sequences could be used to better identify accurate evolutionary models. We subsampled from available ortholog sequences and measured the distribution of observed relationships between paralogs produced across hundreds of models inferred from the subsamples. We observed two important phenomena. First, the reproducibility of an all-sequence, single-alignment reconstruction, measured by comparing topologies inferred from 90% subsamples, directly correlates with the accuracy of that single-alignment reconstruction, producing a measurable value for something that has been traditionally unknowable. Second, topologies that are most consistent with the observations made in the ensemble are more accurate and we present a meta algorithm that exploits this property to improve model accuracy.

Proteome-Level Analysis Indicates Global Mechanisms for Post-Translational Regulation of RRM Domains.

RRM, or RNA-recognition motif, domains are the largest class of single-stranded RNA binding domains in the human proteome and play important roles in RNA processing, splicing, export, stability, packaging, and degradation. Using a current database of post-translational modifications (PTMs), ProteomeScout, we found that RRM domains are also one of the most heavily modified domains in the human proteome. Here, we present two interesting findings about RRM domain modifications, found by mapping known PTMs onto RRM domain alignments and structures. First, we find significant overlap of ubiquitination and acetylation within RRM domains, suggesting the possibility for ubiquitination-acetylation crosstalk. Additionally, an analysis of quantitative study of ubiquitination changes in response to proteasome inhibition highlights the uniqueness of RRM domain ubiquitination - RRM domain ubiquitination decreases in response to proteasome inhibition, whereas the majority of sites increase. Second, we found conservation of tyrosine phosphorylation within the RNP1 and RNP2 consensus sequences, which coordinate RNA binding - suggesting a possible role for regulation of RNA binding by tyrosine kinase signaling. These observations suggest there are unique regulatory mechanisms of RRM function that have yet to be uncovered and that the RRM domain represents a model system for further studies on understanding PTM crosstalk.

High-Resolution Identification of Specificity Determining Positions in the LacI Protein Family Using Ensembles of Sub-Sampled Alignments.

Since the advent of large-scale genomic sequencing, and the consequent availability of large numbers of homologous protein sequences, there has been burgeoning development of methods for extracting functional information from multiple sequence alignments (MSAs). One type of analysis seeks to identify specificity determining positions (SDPs) based on the assumption that such positions are highly conserved within groups of sequences sharing functional specificity, but conserved to different amino acids in different specificity groups. This unsupervised approach to utilizing evolutionary information may elucidate mechanisms of specificity in protein-protein interactions, catalytic activity of enzymes, sensitivity to allosteric regulation, and other types of protein functionality. We present an analysis of SDPs in the LacI family of transcriptional regulators in which we 1) relax the constraint that all specificity groups must contribute to SDP signal, and 2) use a novel approach to robust treatment of sequence alignment uncertainty based on sub-sampling. We find that the vast majority of SDP signal occurs at positions with a conservation pattern that significantly complicates detection by previously described methods. This pattern, which we term "partial SDP", consists of the commonly accepted SDP conservation pattern among a subset of specificity groups and strong degeneracy among the rest. An upshot of this fact is that the SDP complement of every specificity group appears to be unique. Additionally, sub-sampling gives us the ability to assign a confidence interval to the SDP score, as well as increase fidelity, as compared to analysis of a single, comprehensive alignment-the current standard in multiple sequence alignment methodologies.

Injury-induced HDAC5 nuclear export is essential for axon regeneration.

Reactivation of a silent transcriptional program is a critical step in successful axon regeneration following injury. Yet how such a program is unlocked after injury remains largely unexplored. We found that axon injury in peripheral sensory neurons elicits a back-propagating calcium wave that invades the soma and causes nuclear export of HDAC5 in a PKCµ-dependent manner. Injury-induced HDAC5 nuclear export enhances histone acetylation to activate a proregenerative gene-expression program. HDAC5 nuclear export is required for axon regeneration, as expression of a nuclear-trapped HDAC5 mutant prevents axon regeneration, whereas enhancing HDAC5 nuclear export promotes axon regeneration in vitro and in vivo. Components of this HDAC5 pathway failed to be activated in a model of central nervous system injury. These studies reveal a signaling mechanism from the axon injury site to the soma that controls neuronal growth competence and suggest a role for HDAC5 as a transcriptional switch controlling axon regeneration.

Accounting for noise when clustering biological data.

Clustering is a powerful and commonly used technique that organizes and elucidates the structure of biological data. Clustering data from gene expression, metabolomics and proteomics experiments has proven to be useful at deriving a variety of insights, such as the shared regulation or function of biochemical components within networks. However, experimental measurements of biological processes are subject to substantial noise-stemming from both technical and biological variability-and most clustering algorithms are sensitive to this noise. In this article, we explore several methods of accounting for noise when analyzing biological data sets through clustering. Using a toy data set and two different case studies-gene expression and protein phosphorylation-we demonstrate the sensitivity of clustering algorithms to noise. Several methods of accounting for this noise can be used to establish when clustering results can be trusted. These methods span a range of assumptions about the statistical properties of the noise and can therefore be applied to virtually any biological data source.

Comparative genomics of NAD biosynthesis in cyanobacteria.

Biosynthesis of NAD(P) cofactors is of special importance for cyanobacteria due to their role in photosynthesis and respiration. Despite significant progress in understanding NAD(P) biosynthetic machinery in some model organisms, relatively little is known about its implementation in cyanobacteria. We addressed this problem by a combination of comparative genome analysis with verification experiments in the model system of Synechocystis sp. strain PCC 6803. A detailed reconstruction of the NAD(P) metabolic subsystem using the SEED genomic platform (http://theseed.uchicago.edu/FIG/index.cgi) helped us accurately annotate respective genes in the entire set of 13 cyanobacterial species with completely sequenced genomes available at the time. Comparative analysis of operational variants implemented in this divergent group allowed us to elucidate both conserved (de novo and universal pathways) and variable (recycling and salvage pathways) aspects of this subsystem. Focused genetic and biochemical experiments confirmed several conjectures about the key aspects of this subsystem. (i) The product of the slr1691 gene, a homolog of Escherichia coli gene nadE containing an additional nitrilase-like N-terminal domain, is a NAD synthetase capable of utilizing glutamine as an amide donor in vitro. (ii) The product of the sll1916 gene, a homolog of E. coli gene nadD, is a nicotinic acid mononucleotide-preferring adenylyltransferase. This gene is essential for survival and cannot be compensated for by an alternative nicotinamide mononucleotide (NMN)-preferring adenylyltransferase (slr0787 gene). (iii) The product of the slr0788 gene is a nicotinamide-preferring phosphoribosyltransferase involved in the first step of the two-step non-deamidating utilization of nicotinamide (NMN shunt). (iv) The physiological role of this pathway encoded by a conserved gene cluster, slr0787-slr0788, is likely in the recycling of endogenously generated nicotinamide, as supported by the inability of this organism to utilize exogenously provided niacin. Positional clustering and the co-occurrence profile of the respective genes across a diverse collection of cellular organisms provide evidence of horizontal transfer events in the evolutionary history of this pathway.

Ribosylnicotinamide kinase domain of NadR protein: identification and implications in NAD biosynthesis.

NAD is an indispensable redox cofactor in all organisms. Most of the genes required for NAD biosynthesis in various species are known. Ribosylnicotinamide kinase (RNK) was among the few unknown (missing) genes involved with NAD salvage and recycling pathways. Using a comparative genome analysis involving reconstruction of NAD metabolism from genomic data, we predicted and experimentally verified that bacterial RNK is encoded within the 3' region of the nadR gene. Based on these results and previous data, the full-size multifunctional NadR protein (as in Escherichia coli) is composed of (i) an N-terminal DNA-binding domain involved in the transcriptional regulation of NAD biosynthesis, (ii) a central nicotinamide mononucleotide adenylyltransferase (NMNAT) domain, and (iii) a C-terminal RNK domain. The RNK and NMNAT enzymatic activities of recombinant NadR proteins from Salmonella enterica serovar Typhimurium and Haemophilus influenzae were quantitatively characterized. We propose a model for the complete salvage pathway from exogenous N-ribosylnicotinamide to NAD which involves the concerted action of the PnuC transporter and NRK, followed by the NMNAT activity of the NadR protein. Both the pnuC and nadR genes were proven to be essential for the growth and survival of H. influenzae, thus implicating them as potential narrow-spectrum drug targets.