Amino acid signature enables proteins to recognize modified tRNA

Prion-like Aggregation of the Heptapeptide GNNQQNY into Amyloid Nanofiber Is Governed by Configuration Entropy

A major cause of prion infectivity is the early formation of small, fibril-like aggregates consisting of the heptapeptide GNNQQNY. The prion aggregates exhibit a unique stacking mode in which the hydrophobic tyrosine (Y) is exposed outward, forming a bilayer β-sheet-stacking zipper structure. This stacking mode of the prion peptides, termed "Y-outward" structure for convenience, goes against the common understanding that, for other amyloid-forming peptides, the hydrophobic residues should be hidden within the peptide fibril, referred to as "Y-inward" structure. To explore the extraordinary stacking behaviors of the prion GNNQQNY peptides, two fibril models are constructed in a fashion of "Y-outward" and "Y-inward" stackings and then studied in silico to examine their thermodynamic stabilities and disaggregation pathways. The "Y-inward" structure indeed exhibits stronger thermodynamic stability than the "Y-outward" structure, according to potential energy and stacking energy calculations. To show how the peptide fibrils dissociate, we illustrated two disaggregation pathways. A dihedral-based free energy landscape was then calculated to examine the conformational degrees of freedom of the GNNQQNY chains in the "Y-outward" and "Y-inward" structures. Peptide chains lose more configurational entropy in the "Y-inward" structure than in the "Y-outward" structure, indicating that the prion peptides are prone to aggregate in a fashion of "Y-outward" stacking pattern due to its low conformational constraints. The prion-like aggregation of the GNNQQNY peptides into amyloid fibrils is primarily governed by the configuration entropy.

Design of 8-mer peptides that block Clostridioides difficile toxin A in intestinal cells

Infections by Clostridioides difficile, a bacterium that targets the large intestine (colon), impact a large number of people worldwide. Bacterial colonization is mediated by two exotoxins: toxins A and B. Short peptides that can be delivered to the gut and inhibit the biocatalytic activity of these toxins represent a promising therapeutic strategy to prevent and treat C. diff. infection. We describe an approach that combines a Peptide Binding Design (PepBD) algorithm, molecular-level simulations, a rapid screening assay to evaluate peptide:toxin binding, a primary human cell-based assay, and surface plasmon resonance (SPR) measurements to develop peptide inhibitors that block Toxin A in colon epithelial cells. One peptide, SA1, is found to block TcdA toxicity in primary-derived human colon (large intestinal) epithelial cells. SA1 binds TcdA with a KD of 56.1 ± 29.8 nM as measured by surface plasmon resonance (SPR).

Bacteriophage Infection of the Marine Bacterium Shewanella glacialimarina Induces Dynamic Changes in tRNA Modifications

Viruses are obligate intracellular parasites that, throughout evolution, have adapted numerous strategies to control the translation machinery, including the modulation of post-transcriptional modifications (PTMs) on transfer RNA (tRNA). PTMs are critical translation regulators used to further host immune responses as well as the expression of viral proteins. Yet, we lack critical insight into the temporal dynamics of infection-induced changes to the tRNA modification landscape (i.e., 'modificome'). In this study, we provide the first comprehensive quantitative characterization of the tRNA modificome in the marine bacterium Shewanella glacialimarina during Shewanella phage 1/4 infection. Specifically, we show that PTMs can be grouped into distinct categories based on modification level changes at various infection stages. Furthermore, we observe a preference for the UAC codon in viral transcripts expressed at the late stage of infection, which coincides with an increase in queuosine modification. Queuosine appears exclusively on tRNAs with GUN anticodons, suggesting a correlation between phage codon usage and PTM modification. Importantly, this work provides the basis for further studies into RNA-based regulatory mechanisms employed by bacteriophages to control the prokaryotic translation machinery.

Design of 8-mer Peptides that Block Clostridioides difficile Toxin A in Intestinal Cells

Clostridioides difficile ( C. diff .) is a bacterium that causes severe diarrhea and inflammation of the colon. The pathogenicity of C. diff . infection is derived from two major toxins, toxins A (TcdA) and B (TcdB). Peptide inhibitors that can be delivered to the gut to inactivate these toxins are an attractive therapeutic strategy. In this work, we present a new approach that combines a pep tide b inding d esign algorithm (PepBD), molecular-level simulations, rapid screening of candidate peptides for toxin binding, a primary human cell-based assay, and surface plasmon resonance (SPR) measurements to develop peptide inhibitors that block the glucosyltransferase activity of TcdA by targeting its glucosyltransferase domain (GTD). Using PepBD and explicit-solvent molecular dynamics simulations, we identified seven candidate peptides, SA1-SA7. These peptides were selected for specific TcdA GTD binding through a custom solid-phase peptide screening system, which eliminated the weaker inhibitors SA5-SA7. The efficacies of SA1-SA4 were then tested using a trans-epithelial electrical resistance (TEER) assay on monolayers of the human gut epithelial culture model. One peptide, SA1, was found to block TcdA toxicity in primary-derived human jejunum (small intestinal) and colon (large intestinal) epithelial cells. SA1 bound TcdA with a K D of 56.1 ± 29.8 nM as measured by surface plasmon resonance (SPR).

Significance Statement

Infections by Clostridioides difficile , a bacterium that targets the large intestine (colon), impact a significant number of people worldwide. Bacterial colonization is mediated by two exotoxins: toxins A and B. Short peptides that can inhibit the biocatalytic activity of these toxins represent a promising strategy to prevent and treat C. diff . infection. We describe an approach that combines a Peptide B inding D esign (PepBD) algorithm, molecular-level simulations, a rapid screening assay to evaluate peptide:toxin binding, a primary human cell-based assay, and surface plasmon resonance (SPR) measurements to develop peptide inhibitors that block Toxin A in small intestinal and colon epithelial cells. Importantly, our designed peptide, SA1, bound toxin A with nanomolar affinity and blocked toxicity in colon cells.

Sequence patterns and signatures: Computational and experimental discovery of amyloid-forming peptides

Screening amino acid sequence space via experiments to discover peptides that self-assemble into amyloid fibrils is challenging. We have developed a computational peptide assembly design (PepAD) algorithm that enables the discovery of amyloid-forming peptides. Discontinuous molecular dynamics (DMD) simulation with the PRIME20 force field combined with the FoldAmyloid tool is used to examine the fibrilization kinetics of PepAD-generated peptides. PepAD screening of ∼10,000 7-mer peptides resulted in twelve top-scoring peptides with two distinct hydration properties. Our studies revealed that eight of the twelve in silico discovered peptides spontaneously form amyloid fibrils in the DMD simulations and that all eight have at least five residues that the FoldAmyloid tool classifies as being aggregation-prone. Based on these observations, we re-examined the PepAD-generated peptides in the sequence pool returned by PepAD and extracted five sequence patterns as well as associated sequence signatures for the 7-mer amyloid-forming peptides. Experimental results from Fourier transform infrared spectroscopy (FTIR), thioflavin T (ThT) fluorescence, circular dichroism (CD), and transmission electron microscopy (TEM) indicate that all the peptides predicted to assemble in silico assemble into antiparallel β-sheet nanofibers in a concentration-dependent manner. This is the first attempt to use a computational approach to search for amyloid-forming peptides based on customized settings. Our efforts facilitate the identification of β-sheet-based self-assembling peptides, and contribute insights towards answering a fundamental scientific question: "What does it take, sequence-wise, for a peptide to self-assemble?".

Computational Design and Experimental Validation of ACE2-Derived Peptides as SARS-CoV-2 Receptor Binding Domain Inhibitors

The COVID-19 pandemic has caused significant social and economic disruption across the globe. Cellular entry of SARS-CoV-2 into the human body is mediated via binding of the Receptor Binding Domain (RBD) on the viral Spike protein (SARS-CoV-2 RBD) to Angiotensin-Converting Enzyme 2 (ACE2) expressed on host cells. Molecules that can disrupt ACE2:RBD interactions are attractive therapeutic candidates to prevent virus entry into human cells. A computational strategy that combines our Peptide Binding Design (PepBD) algorithm with atomistic molecular dynamics simulations was used to design new inhibitory peptide candidates via sequence iteration starting with a 23-mer peptide, referred to as SBP1. SBP1 is derived from a region of the ACE2 Peptidase Domain α1 helix that binds to the SARS-CoV-2 RBD of the initial Wuhan-Hu-1 strain. Three peptides demonstrated a solution-phase RBD-binding dissociation constant in the micromolar range during tryptophan fluorescence quenching experiments, one peptide did not bind, and one was insoluble at micromolar concentrations. However, in competitive ELISA assays, none of these peptides could outcompete ACE2 binding to SARS-CoV-2-RBD up to concentrations of 50 μM, similar to the parent SBP1 peptide which also failed to outcompete ACE2:RBD binding. Molecular dynamics simulations suggest that P4 would have a good binding affinity for the RBD domain of Beta-B.1.351, Gamma-P.1, Kappa-B.1.617.1, Delta-B.1.617.2, and Omicron-B.1.1.529 variants, but not the Alpha variant. Consistent with this, P4 bound Kappa-B.1.617.1 and Delta-B.1.617.2 RBD with micromolar affinity in tryptophan fluorescence quenching experiments. Collectively, these data show that while relatively short unstructured peptides can bind to SARS-CoV-2 RBD with moderate affinity, they are incapable of outcompeting the strong interactions between RBD and ACE2.

Physical Chemistry of a Single tRNA-Modified Nucleoside Regulates Decoding of the Synonymous Lysine Wobble Codon and Affects Type 2 Diabetes

The 2-methylthio-modification (ms²-) of N⁶-threonylcarbonyladenosine (t⁶A₃₇) at position-37 (ms²t⁶A₃₇) in tRNA_UUU^Lys3 provides the needed stability between the tRNA anticodon and the human insulin mRNA codon AAG during translation, as determined by molecular dynamics simulation. Single-nucleoside polymorphisms of the human gene for the enzyme, Cdkal1 that post-transcriptionally modifies t⁶A₃₇ to ms²t⁶A₃₇ in tRNA_UUU^Lys3, correlate with type 2 diabetes mellitus. Without the ms²-modification, tRNA_UUU^Lys3 is incapable of correctly translating the insulin mRNA AAG codon for lysine at the site of protease cleavage between the A-chain and the C-peptide. By enhancing anticodon/codon cross-strand stacking, the ms²-modification adds stability through van der Waals interactions and dehydration of the ASL loop and cavity of the anticodon/codon minihelix but does not add hydrogen bonding of any consequence. Thus, the modifying enzyme Cdkal1, by adding a crucial ms²-group to tRNA_UUU^Lys3-t⁶A₃₇, facilitates the decoding of the AAG codon and enables human pancreatic islets to correctly translate insulin mRNA.

In Silico Identification and Experimental Validation of Peptide-Based Inhibitors Targeting Clostridium difficile Toxin A

Clostridium difficile infection is mediated by two major exotoxins: toxins A (TcdA) and B (TcdB). Inhibiting the biocatalytic activities of these toxins with targeted peptide-based drugs can reduce the risk of C. difficile infection. In this work, we used a computational strategy that integrates a peptide binding design (PepBD) algorithm and explicit-solvent atomistic molecular dynamics simulation to determine promising toxin A-targeting peptides that can recognize and bind to the catalytic site of the TcdA glucosyltransferase domain (GTD). Our simulation results revealed that two out of three in silico discovered peptides, viz. the neutralizing peptides A (NPA) and B (NPB), exhibit lower binding free energies when bound to the TcdA GTD than the phage-display discovered peptide, viz. the reference peptide (RP). These peptides may serve as potential inhibitors against C. difficile infection. The efficacy of the peptides RP, NPA, and NPB to neutralize the cytopathic effects of TcdA was tested in vitro in human jejunum cells. Both phage-display peptide RP and in silico peptide NPA were found to exhibit strong toxin-neutralizing properties, thereby preventing the TcdA toxicity. However, the in silico peptide NPB demonstrates a relatively low efficacy against TcdA.

De novo design of peptides that coassemble into β sheet-based nanofibrils

Peptides’ hierarchical coassembly into nanostructures enables controllable fabrication of multicomponent biomaterials. In this work, we describe a computational and experimental approach to design pairs of charge-complementary peptides that selectively coassemble into β-sheet nanofibers when mixed together but remain unassembled when isolated separately. The key advance is a peptide coassembly design (PepCAD) algorithm that searches for pairs of coassembling peptides. Six peptide pairs are identified from a pool of ~10⁶ candidates via the PepCAD algorithm and then subjected to DMD/PRIME20 simulations to examine their co-/self-association kinetics. The five pairs that spontaneously aggregate in kinetic simulations selectively coassemble in biophysical experiments, with four forming β-sheet nanofibers and one forming a stable nonfibrillar aggregate. Solid-state NMR, which is applied to characterize the coassembling pairs, suggests that the in silico peptides exhibit a higher degree of structural order than the previously reported CATCH(+/−) peptides.

A ChemE Grows in Brooklyn

I profile my personal and professional journey from being a girl of the 1950s, with expectations typical for the times, to a chemical engineering professor and still-enthusiastic researcher. I describe my family, my early education, my college and graduate school training in physics, my postdoc years in chemistry, and my subsequent transformation into a chemical engineering faculty member-one of the first women to be appointed to a chemical engineering faculty in the United States. I focus on the events that shaped me, the people who noticed and supported me, and the environment for women scientists and engineers in what some would call the "early days." My initial research activities centered on applications of statistical mechanics to predict phase equilibria in simple systems. Over time, my interests evolved to focus on applying molecule-level computer simulations to systems of interest to chemical engineers, e.g., hydrocarbons and polymers. Eventually, spurred on by my personal interest in amyloid diseases and my wish to make a contribution to human health, I turned to more biologically oriented problems having to do with protein aggregation and protein design. I give a candid assessment of my strengths and weaknesses, successes and failures. Finally, I share the most valuable lessons that I have learned over a lifetime of professional and personal experience.

Computational evolution of an RNA-binding protein towards enhanced oxidized-RNA binding

The oxidation of RNA has been implicated in the development of many diseases. Among the four ribonucleotides, guanosine is the most susceptible to oxidation, resulting in the formation of 8-oxo-7,8-dihydroguanosine (8-oxoG). Despite the limited knowledge about how cells regulate the detrimental effects of oxidized RNA, cellular factors involved in its regulation have begun to be identified. One of these factors is polynucleotide phosphorylase (PNPase), a multifunctional enzyme implicated in RNA turnover. In the present study, we have examined the interaction of PNPase with 8-oxoG in atomic detail to provide insights into the mechanism of 8-oxoG discrimination. We hypothesized that PNPase subunits cooperate to form a binding site using the dynamic SFF loop within the central channel of the PNPase homotrimer. We evolved this site using a novel approach that initially screened mutants from a library of beneficial mutations and assessed their interactions using multi-nanosecond Molecular Dynamics simulations. We found that evolving this single site resulted in a fold change increase in 8-oxoG affinity between 1.2 and 1.5 and/or selectivity between 1.5 and 1.9. In addition to the improvement in 8-oxoG binding, complementation of K12 Δpnp with plasmids expressing mutant PNPases caused increased cell tolerance to H₂O₂. This observation provides a clear link between molecular discrimination of RNA oxidation and cell survival. Moreover, this study provides a framework for the manipulation of modified-RNA protein readers, which has potential application in synthetic biology and epitranscriptomics.

Extended Concerted Rotation Technique Enhances the Sampling Efficiency of the Computational Peptide-Design Algorithm

To enhance the sampling efficiency of our computational peptide-design algorithm in conformational space, the concerted rotation (CONROT) technique is extended to enable larger conformational perturbations of peptide chains. This allows us to make relatively large peptide conformation changes during the process of designing peptide sequences to bind with high affinity to a specific target. Searches conducted using the new algorithm identified six potential λ N(2-22) peptide variants, called B1-B6, which bind to boxB RNA with high affinity. The results of explicit-solvent atomistic molecular dynamics simulations revealed that four of the evolved peptides, viz. B1, B2, B3, and B5, are excellent candidate binders to the target boxB RNA as they have lower binding free energies than the original λ N(2-22) peptide. Three of the four peptides, B2, B3, and B5, result from searches that contain both sequence and conformation changes, indicating that adding backbone motif changes to the peptide-design algorithm improves its performance considerably.

The Importance of Being Modified: The Role of RNA Modifications in Translational Fidelity

The posttranscriptional modifications of tRNA's anticodon stem and loop (ASL) domain represent a third level, a third code, to the accuracy and efficiency of translating mRNA codons into the correct amino acid sequence of proteins. Modifications of tRNA's ASL domain are enzymatically synthesized and site specifically located at the anticodon wobble position-34 and 3'-adjacent to the anticodon at position-37. Degeneracy of the 64 Universal Genetic Codes and the limitation in the number of tRNA species require some tRNAs to decode more than one codon. The specific modification chemistries and their impact on the tRNA's ASL structure and dynamics enable one tRNA to decode cognate and "wobble codons" or to expand recognition to synonymous codons, all the while maintaining the translational reading frame. Some modified nucleosides' chemistries prestructure tRNA to read the two codons of a specific amino acid that shares a twofold degenerate codon box, and other chemistries allow a different tRNA to respond to all four codons of a fourfold degenerate codon box. Thus, tRNA ASL modifications are critical and mutations in genes for the modification enzymes and tRNA, the consequences of which is a lack of modification, lead to mistranslation and human disease. By optimizing tRNA anticodon chemistries, structure, and dynamics in all organisms, modifications ensure translational fidelity of mRNA transcripts.

Adding energy minimization strategy to peptide-design algorithm enables better search for RNA-binding peptides: Redesigned λ N peptide binds boxB RNA

Our previously developed peptide-design algorithm was improved by adding an energy minimization strategy which allows the amino acid sidechains to move in a broad configuration space during sequence evolution. In this work, the new algorithm was used to generate a library of 21-mer peptides which could substitute for λ N peptide in binding to boxB RNA. Six potential peptides were obtained from the algorithm, all of which exhibited good binding capability with boxB RNA. Atomistic molecular dynamics simulations were then conducted to examine the ability of the λ N peptide and three best evolved peptides, viz. Pept01, Pept26, and Pept28, to bind to boxB RNA. Simulation results demonstrated that our evolved peptides are better at binding to boxB RNA than the λ N peptide. Sequence searches using the old (without energy minimization strategy) and new (with energy minimization strategy) algorithms confirm that the new algorithm is more effective at finding good RNA-binding peptides than the old algorithm. © 2016 Wiley Periodicals, Inc.

Simulation study of the ability of a computationally-designed peptide to recognize target tRNALys3 and other decoy tRNAs

In this paper, we investigate the ability of our computationally-designed peptide, Pept10 (PNWNGNRWLNNCLRG), to recognize the anticodon stem and loop (ASL) domain of the hypermodified tRNA^Lys3 (mcm⁵ s² U₃₄ ,ms² t⁶ A₃₇ ), a reverse transcription primer of HIV replication. Five other ASLs, the singly modified ASL^Lys3 (ms² t⁶ A₃₇ ), ASL^Lys3 (s² U₃₄ ), ASL^Lys3 (Ψ₃₉ ), ASL^Lys1,2 (t⁶ A₃₇ ), and ASL^Glu (s² U₃₄ ), were used as decoys. Explicit-solvent atomistic molecular dynamics simulations were performed to examine the process of binding of Pept10 with the target ASL^Lys3 (mcm⁵ s² U₃₄ ,ms² t⁶ A₃₇ ) and the decoy ASLs. Simulation results demonstrated that Pept10 is capable of recognizing the target ASL^Lys3 (mcm⁵ s² U₃₄ ,ms² t⁶ A₃₇ ) as well as one of the decoys, ASL^Lys3 (Ψ₃₉ ), but screens out the other four decoy ASLs. The interchain van der Waals (VDW) and charge-charge (ELE + EGB) energies for the two best complexes were evaluated to shed light on the molecular recognition mechanism between Pept10 and ASLs. The results indicated that Pept10 recognizes and binds to the target ASL^Lys3 (mcm⁵ s² U₃₄ ,ms² t⁶ A₃₇ ) through residues W₃ and R₇ which interact with the nucleotides mcm⁵ s² U₃₄ , U₃₅ , and ms² t⁶ A₃₇ via the interchain VDW energy. Pept10 also recognizes the decoy ASL^Lys3 (Ψ₃₉ ) through residue R₁₄ which contacts the nucleotide U₃₆ via the interchain VDW energy. Regardless of the type of ASL, the positively charged arginines on Pept10 are attracted to the negatively charged phosphate linkages on the ASL via the interchain ELE + EGB energy, thereby enhancing the binding affinity.

Designing peptide sequences in flexible chain conformations to bind RNA: a search algorithm combining Monte Carlo, self-consistent mean field and concerted rotation techniques

A search algorithm combining Monte Carlo, self-consistent mean field, and concerted rotation techniques was developed to discover peptide sequences that are reasonable HIV drug candidates due to their exceptional binding to human tRNAUUU(Lys3), the primer of HIV replication. The search algorithm allows for iteration between sequence mutations and conformation changes during sequence evolution. Searches conducted for different classes of peptides identified several potential peptide candidates. Analysis of the energy revealed that the asparagine and cysteine at residues 11 and 12 play important roles in "recognizing" tRNA(Lys3) via van der Waals interactions, contributing to binding specificity. Arginines preferentially attract the phosphate linkage via charge-charge interaction, contributing to binding affinity. Evaluation of the RNA/peptide complex's structure revealed that adding conformation changes to the search algorithm yields peptides with better binding affinity and specificity to tRNA(Lys3) than a previous mutation-only algorithm.

Introducing folding stability into the score function for computational design of RNA-binding peptides boosts the probability of success

A computational strategy that integrates our peptide search algorithm with atomistic molecular dynamics simulation was used to design rational peptide drugs that recognize and bind to the anticodon stem and loop domain (ASL(Lys3)) of human tRNAUUULys3 for the purpose of interrupting HIV replication. The score function of the search algorithm was improved by adding a peptide stability term weighted by an adjustable factor λ to the peptide binding free energy. The five best peptide sequences associated with five different values of λ were determined using the search algorithm and then input in atomistic simulations to examine the stability of the peptides' folded conformations and their ability to bind to ASL(Lys3). Simulation results demonstrated that setting an intermediate value of λ achieves a good balance between optimizing the peptide's binding ability and stabilizing its folded conformation during the sequence evolution process, and hence leads to optimal binding to the target ASL(Lys3). Thus, addition of a peptide stability term significantly improves the success rate for our peptide design search.

tRNA wobble modifications and protein homeostasis

tRNA is a central component of the protein synthesis machinery in the cell. In living cells, tRNAs undergo numerous post-transcriptional modifications. In particular, modifications at the anticodon loop play an important role in ensuring efficient protein synthesis, maintaining protein homeostasis, and helping cell adaptation and survival. Hypo-modification of the wobble position of the tRNA anticodon loop is of particular relevance for translation regulation and is implicated in various human diseases. In this review we summarize recent evidence of how methyl and thiol modifications in eukaryotic tRNA at position 34 affect cellular fitness and modulate regulatory circuits at normal conditions and under stress.

Exploiting tRNAs to Boost Virulence

Transfer RNAs (tRNAs) are powerful small RNA entities that are used to translate nucleotide language of genes into the amino acid language of proteins. Their near-uniform length and tertiary structure as well as their high nucleotide similarity and post-transcriptional modifications have made it difficult to characterize individual species quantitatively. However, due to the central role of the tRNA pool in protein biosynthesis as well as newly emerging roles played by tRNAs, their quantitative assessment yields important information, particularly relevant for virus research. Viruses which depend on the host protein expression machinery have evolved various strategies to optimize tRNA usage—either by adapting to the host codon usage or encoding their own tRNAs. Additionally, several viruses bear tRNA-like elements (TLE) in the 5′- and 3′-UTR of their mRNAs. There are different hypotheses concerning the manner in which such structures boost viral protein expression. Furthermore, retroviruses use special tRNAs for packaging and initiating reverse transcription of their genetic material. Since there is a strong specificity of different viruses towards certain tRNAs, different strategies for recruitment are employed. Interestingly, modifications on tRNAs strongly impact their functionality in viruses. Here, we review those intersection points between virus and tRNA research and describe methods for assessing the tRNA pool in terms of concentration, aminoacylation and modification.

Unreported intrinsic disorder in proteins: Building connections to the literature on IDPs

This review opens a new series entitled “Unreported intrinsic disorder in proteins.” The goal of this series is to bring attention of researchers to an interesting phenomenon of missed (or overlooked, or ignored, or unreported) disorder. This series serves as a companion to “Digested Disorder” which provides a quarterly review of papers on intrinsically disordered proteins (IDPs) found by standard literature searches. The need for this alternative series results from the observation that there are numerous publications that describe IDPs (or hybrid proteins with ordered and disordered regions) yet fail to recognize many of the key discoveries and publications in the IDP field. By ignoring the body of work on IDPs, such publications often fail to relate their findings to prior discoveries or fail to explore the obvious implications of their work. Thus, the goal of this series is not only to review these very interesting and important papers, but also to point out how each paper relates to the IDP field and show how common tools in the IDP field can readily take the findings in new directions or provide a broader context for the reported findings.