Adam J. Hockenberry

Synthetic in vitro circuits

Inspired by advances in the ability to construct programmable circuits in living organisms, in vitro circuits are emerging as a viable platform for designing, understanding, and exploiting dynamic biochemical circuitry. In vitro systems allow researchers to directly access and manipulate biomolecular parts without the unwieldy complexity and intertwined dependencies that often exist in vivo. Experimental and computational foundations in DNA, DNA/RNA, and DNA/RNA/protein based circuitry have given rise to systems with more than 100 programmed molecular constituents. Functionally, they have diverse capabilities including: complex mathematical calculations, associative memory tasks, and sensing of small molecules. Progress in this field is showing that cell-free synthetic biology is a versatile testing ground for understanding native biological circuits and engineering novel functionality.

N-Methyl-d-aspartate Receptor Mechanosensitivity Is Governed by C Terminus of NR2B Subunit

Background: The NMDA receptor mediates stretch-induced calcium influx and resulting neuronal excitotoxicity. Results: Calcium influx through NMDA receptors following stretch is reduced in cultures expressing NR2B C-terminal mutations. Conclusion: Mechanosensitivity of NMDA receptors is dependent on the NR2B subunit and PKC activity at the NR2B C terminus. Significance: These data provide insight into NMDA receptor subtype-specific mechanisms that dictate response to neuronal stretch. N-Methyl-d-aspartate receptors (NMDARs), critical mediators of both physiologic and pathologic neurological signaling, have previously been shown to be sensitive to mechanical stretch through the loss of its native Mg2+ block. However, the regulation of this mechanosensitivity has yet to be further explored. Furthermore, as it has become apparent that NMDAR-mediated signaling is dependent on specific NMDAR subtypes, as governed by the identity of the NR2 subunit, a crucial unanswered question is the role of subunit composition in observed NMDAR mechanosensitivity. Here, we used a recombinant system to assess the mechanosensitivity of specific subtypes and demonstrate that the mechanosensitive property is uniquely governed by the NR2B subunit. NR1/NR2B NMDARs displayed significant stretch sensitivity, whereas NR1/NR2A NMDARs did not respond to stretch. Furthermore, NR2B mechanosensitivity was regulated by PKC activity, because PKC inhibition reduced stretch responses in transfected HEK 293 cells and primary cortical neurons. Finally, using NR2B point mutations, we identified a PKC phosphorylation site, Ser-1323 on NR2B, as a unique critical regulator of stretch sensitivity. These data suggest that the selective mechanosensitivity of NR2B can significantly impact neuronal response to traumatic brain injury and illustrate that the mechanical tone of the neuron can be dynamically regulated by PKC activity.

NR2A and NR2B subunits differentially mediate MAP kinase signaling and mitochondrial morphology following excitotoxic insult

NMDA receptors are essential for neurotransmission and key mediators of synaptic signaling, but they can also trigger deleterious degenerative processes that lead to cell death. Growing evidence suggests that selective blockade of the heterogeneous subunits that comprise the NMDA receptor may enable better control of pharmacotherapies for treating neurological diseases and injuries. We investigated the relationship between NMDAR activation, MAPK signaling, and mitochondrial shape following an excitotoxic insult. NR2A- and NR2B-containing NMDARs differentially mediated acute changes in cytosolic calcium, alterations in mitochondrial morphology, and phosphorylation of the MAPKs ERK and JNK. Activation of NR2A-containing NMDARs was associated with JNK phosphorylation that was neuroprotective in neuronal cultures subjected to excitotoxicity. In contrast, activation of NR2B-containing NMDARs triggered calcium accumulation in mitochondria that was strongly associated with mitochondrial swelling and neuronal cell death. Indeed, while blockade of NR2B-containing receptors was neuroprotective, this protection was lost when NR2A-initiated JNK phosphorylation was inhibited. Given the modest selectivity of the NR2A inhibitor, NVP-AAM077, the results highlight the significance of the relative, rather than absolute, activation of these two NMDA subtypes in modulating cell death pathways. Therefore, the balance between concurrent activation of NR2B-containing and NR2A-containing NMDARs dictates neuronal fate following excitotoxicity.

Quantifying Position-Dependent Codon Usage Bias

Although the mapping of codon to amino acid is conserved across nearly all species, the frequency at which synonymous codons are used varies both between organisms and between genes from the same organism. This variation affects diverse cellular processes including protein expression, regulation, and folding. Here, we mathematically model an additional layer of complexity and show that individual codon usage biases follow a position-dependent exponential decay model with unique parameter fits for each codon. We use this methodology to perform an in-depth analysis on codon usage bias in the model organism Escherichia coli. Our methodology shows that lowly and highly expressed genes are more similar in their codon usage patterns in the 5′-gene regions, but that these preferences diverge at distal sites resulting in greater positional dependency (pD, which we mathematically define later) for highly expressed genes. We show that position-dependent codon usage bias is partially explained by the structural requirements of mRNAs that results in increased usage of A/T rich codons shortly after the gene start. However, we also show that the pD of 4- and 6-fold degenerate codons is partially related to the gene copy number of cognate-tRNAs supporting existing hypotheses that posit benefits to a region of slow translation in the beginning of coding sequences. Lastly, we demonstrate that viewing codon usage bias through a position-dependent framework has practical utility by improving accuracy of gene expression prediction when incorporating positional dependencies into the Codon Adaptation Index model.

Computational investigation of the changing patterns of subtype specific NMDA receptor activation during physiological glutamatergic neurotransmission.

NMDA receptors (NMDARs) are the major mediator of the postsynaptic response during synaptic neurotransmission. The diversity of roles for NMDARs in influencing synaptic plasticity and neuronal survival is often linked to selective activation of multiple NMDAR subtypes (NR1/NR2A-NMDARs, NR1/NR2B-NMDARs, and triheteromeric NR1/NR2A/NR2B-NMDARs). However, the lack of available pharmacological tools to block specific NMDAR populations leads to debates on the potential role for each NMDAR subtype in physiological signaling, including different models of synaptic plasticity. Here, we developed a computational model of glutamatergic signaling at a prototypical dendritic spine to examine the patterns of NMDAR subtype activation at temporal and spatial resolutions that are difficult to obtain experimentally. We demonstrate that NMDAR subtypes have different dynamic ranges of activation, with NR1/NR2A-NMDAR activation sensitive at univesicular glutamate release conditions, and NR2B containing NMDARs contributing at conditions of multivesicular release. We further show that NR1/NR2A-NMDAR signaling dominates in conditions simulating long-term depression (LTD), while the contribution of NR2B containing NMDAR significantly increases for stimulation frequencies that approximate long-term potentiation (LTP). Finally, we show that NR1/NR2A-NMDAR content significantly enhances response magnitude and fidelity at single synapses during chemical LTP and spike timed dependent plasticity induction, pointing out an important developmental switch in synaptic maturation. Together, our model suggests that NMDAR subtypes are differentially activated during different types of physiological glutamatergic signaling, enhancing the ability for individual spines to produce unique responses to these different inputs.

Leveraging genome-wide datasets to quantify the functional role of the anti-Shine-Dalgarno sequence in regulating translation efficiency

Studies dating back to the 1970s established that sequence complementarity between the anti-Shine–Dalgarno (aSD) sequence on prokaryotic ribosomes and the 5′ untranslated region of mRNAs helps to facilitate translation initiation. The optimal location of aSD sequence binding relative to the start codon, the full extents of the aSD sequence and the functional form of the relationship between aSD sequence complementarity and translation efficiency have not been fully resolved. Here, we investigate these relationships by leveraging the sequence diversity of endogenous genes and recently available genome-wide estimates of translation efficiency. We show that—after accounting for predicted mRNA structure—aSD sequence complementarity increases the translation of endogenous mRNAs by roughly 50%. Further, we observe that this relationship is nonlinear, with translation efficiency maximized for mRNAs with intermediate levels of aSD sequence complementarity. The mechanistic insights that we observe are highly robust: we find nearly identical results in multiple datasets spanning three distantly related bacteria. Further, we verify our main conclusions by re-analysing a controlled experimental dataset.

Depletion of Shine-Dalgarno Sequences Within Bacterial Coding Regions Is Expression Dependent

Efficient and accurate protein synthesis is crucial for organismal survival in competitive environments. Translation efficiency (the number of proteins translated from a single mRNA in a given time period) is the combined result of differential translation initiation, elongation, and termination rates. Previous research identified the Shine-Dalgarno (SD) sequence as a modulator of translation initiation in bacterial genes, while codon usage biases are frequently implicated as a primary determinant of elongation rate variation. Recent studies have suggested that SD sequences within coding sequences may negatively affect translation elongation speed, but this claim remains controversial. Here, we present a metric to quantify the prevalence of SD sequences in coding regions. We analyze hundreds of bacterial genomes and find that the coding sequences of highly expressed genes systematically contain fewer SD sequences than expected, yielding a robust correlation between the normalized occurrence of SD sites and protein abundances across a range of bacterial taxa. We further show that depletion of SD sequences within ribosomal protein genes is correlated with organismal growth rates, supporting the hypothesis of strong selection against the presence of these sequences in coding regions and suggesting their association with translation efficiency in bacteria.

Economic insecurity and the rise in gun violence at US schools

Frequent school shootings are a unique US phenomenon that has defied understanding1,2. Uncovering the aetiology of this problem is hampered by the lack of an established dataset3,4. Here we assemble a carefully curated dataset for the period 1990–2013 that is built upon an exhaustive review of existing data and original sources. Using this dataset, we find that the rate of gun violence is time-dependent and that this rate is heightened from 2007 to 2013. We further find that periods of increased shooting rates are significantly correlated with increases in the unemployment rate across different geographic aggregation levels (national, regional and city). Consistent with the hypothesis that increasing uncertainty in the school-to-work transition contributes to school shootings, we find that multiple indicators of economic distress significantly correlate with increases in the rate of gun violence when events at both K12 and post-secondary schools are considered.

NullSeq: A Tool for Generating Random Coding Sequences with Desired Amino Acid and GC Contents

The existence of over- and under-represented sequence motifs in genomes provides evidence of selective evolutionary pressures on biological mechanisms such as transcription, translation, ligand-substrate binding, and host immunity. In order to accurately identify motifs and other genome-scale patterns of interest, it is essential to be able to generate accurate null models that are appropriate for the sequences under study. While many tools have been developed to create random nucleotide sequences, protein coding sequences are subject to a unique set of constraints that complicates the process of generating appropriate null models. There are currently no tools available that allow users to create random coding sequences with specified amino acid composition and GC content for the purpose of hypothesis testing. Using the principle of maximum entropy, we developed a method that generates unbiased random sequences with pre-specified amino acid and GC content, which we have developed into a python package. Our method is the simplest way to obtain maximally unbiased random sequences that are subject to GC usage and primary amino acid sequence constraints. Furthermore, this approach can easily be expanded to create unbiased random sequences that incorporate more complicated constraints such as individual nucleotide usage or even di-nucleotide frequencies. The ability to generate correctly specified null models will allow researchers to accurately identify sequence motifs which will lead to a better understanding of biological processes as well as more effective engineering of biological systems.

Diversity of Translation Initiation Mechanisms across Bacterial Species Is Driven by Environmental Conditions and Growth Demands

&NA; The Shine‐Dalgarno (SD) sequence motif is frequently found upstream of protein coding genes and is thought to be the dominant mechanism of translation initiation used by bacteria. Experimental studies have shown that the SD sequence facilitates start codon recognition and enhances translation initiation by directly interacting with the highly conserved anti‐SD sequence on the 30S ribosomal subunit. However, the proportion of SD‐led genes within a genome varies across species and the factors governing this variation in translation initiation mechanisms remain largely unknown. Here, we conduct a phylogenetically informed analysis and find that species capable of rapid growth contain a higher proportion of SD‐led genes throughout their genomes. We show that SD sequence utilization covaries with a suite of genomic features that are important for efficient translation initiation and elongation. In addition to these endogenous genomic factors, we further show that exogenous environmental factors may influence the evolution of translation initiation mechanisms by finding that thermophilic species contain significantly more SD‐led genes than mesophiles. Our results demonstrate that variation in translation initiation mechanisms across bacterial species is predictable and is a consequence of differential life‐history strategies related to maximum growth rate and environmental‐specific constraints.