An alpha-helical lid guides the target DNA toward catalysis in CRISPR-Cas12a.

CRISPR-Cas12a is a powerful RNA-guided genome-editing system that generates double-strand DNA breaks using its single RuvC nuclease domain by a sequential mechanism in which initial cleavage of the non-target strand is followed by target strand cleavage. How the spatially distant DNA target strand traverses toward the RuvC catalytic core is presently not understood. Here, continuous tens of microsecond-long molecular dynamics and free-energy simulations reveal that an α-helical lid, located within the RuvC domain, plays a pivotal role in the traversal of the DNA target strand by anchoring the crRNA:target strand duplex and guiding the target strand toward the RuvC core, as also corroborated by DNA cleavage experiments. In this mechanism, the REC2 domain pushes the crRNA:target strand duplex toward the core of the enzyme, while the Nuc domain aids the bending and accommodation of the target strand within the RuvC core by bending inward. Understanding of this critical process underlying Cas12a activity will enrich fundamental knowledge and facilitate further engineering strategies for genome editing.

Unveiling the RNA-mediated allosteric activation discloses functional hotspots in CRISPR-Cas13a.

Cas13a is a recent addition to the CRISPR-Cas toolkit that exclusively targets RNA, which makes it a promising tool for RNA detection. It utilizes a CRISPR RNA (crRNA) to target RNA sequences and trigger a composite active site formed by two 'Higher Eukaryotes and Prokaryotes Nucleotide' (HEPN) domains, cleaving any solvent-exposed RNA. In this system, an intriguing form of allosteric communication controls the RNA cleavage activity, yet its molecular details are unknown. Here, multiple-microsecond molecular dynamics simulations are combined with graph theory to decipher this intricate activation mechanism. We show that the binding of a target RNA acts as an allosteric effector, by amplifying the communication signals over the dynamical noise through interactions of the crRNA at the buried HEPN1-2 interface. By introducing a novel Signal-to-Noise Ratio (SNR) of communication efficiency, we reveal critical allosteric residues-R377, N378, and R973-that rearrange their interactions upon target RNA binding. Alanine mutation of these residues is shown to select target RNA over an extended complementary sequence beyond guide-target duplex for RNA cleavage, establishing the functional significance of these hotspots. Collectively our findings offer a fundamental understanding of the Cas13a mechanism of action and pave new avenues for the development of highly selective RNA-based cleavage and detection tools.

New design strategies for ultra-specific CRISPR-Cas13a-based RNA detection with single-nucleotide mismatch sensitivity.

An increasingly pressing need for clinical diagnostics has required the development of novel nucleic acid-based detection technologies that are sensitive, fast, and inexpensive, and that can be deployed at point-of-care. Recently, the RNA-guided ribonuclease CRISPR-Cas13 has been successfully harnessed for such purposes. However, developing assays for detection of genetic variability, for example single-nucleotide polymorphisms, is still challenging and previously described design strategies are not always generalizable. Here, we expanded our characterization of LbuCas13a RNA-detection specificity by performing a combination of experimental RNA mismatch tolerance profiling, molecular dynamics simulations, protein, and crRNA engineering. We found certain positions in the crRNA-target-RNA duplex that are particularly sensitive to mismatches and establish the effect of RNA concentration in mismatch tolerance. Additionally, we determined that shortening the crRNA spacer or modifying the direct repeat of the crRNA leads to stricter specificities. Furthermore, we harnessed our understanding of LbuCas13a allosteric activation pathways through molecular dynamics and structure-guided engineering to develop novel Cas13a variants that display increased sensitivities to single-nucleotide mismatches. We deployed these Cas13a variants and crRNA design strategies to achieve superior discrimination of SARS-CoV-2 strains compared to wild-type LbuCas13a. Together, our work provides new design criteria and Cas13a variants to use in future easier-to-implement Cas13-based RNA detection applications.

Substrate-independent activation pathways of the CRISPR-Cas9 HNH nuclease.

A hallmark of tightly regulated high-fidelity enzymes is that they become activated only after encountering cognate substrates, often by an induced-fit mechanism rather than conformational selection. Upon analysis of molecular dynamics trajectories, we recently discovered that the Cas9 HNH domain exists in three conformations: 1) Y836 (which is two residues away from the catalytic D839 and H840 residues) is hydrogen bonded to the D829 backbone amide, 2) Y836 is hydrogen bonded to the backbone amide of D861 (which is one residue away from the third catalytic residue N863), and 3) Y836 is not hydrogen bonded to either residue. Each of the three conformers differs from the active state of HNH. The conversion between the inactive and active states involves a local unfolding-refolding process that displaces the Cα and side chain of the catalytic N863 residue by ∼5 Å and ∼10 Å, respectively. In this study, we report the two largest principal components of coordinate variance of the HNH domain throughout molecular dynamics trajectories to establish the interconversion pathways of these conformations. We show that conformation 2 is an obligate step between conformations 1 and 3, which are not directly interconvertible without conformation 2. The loss of hydrogen bonding of the Y836 side chain in conformation 3 likely plays an essential role in activation during local unfolding-refolding of an α-helix containing the catalytic N863. Three single Lys-to-Ala mutants appear to eliminate this substrate-independent activation pathway of the wild-type HNH nuclease, thereby enhancing the fidelity of HNH cleavage.

RNA-mediated Allosteric Activation in CRISPR-Cas13a.

Cas13a is a recent addition to the CRISPR-Cas toolkit that exclusively targets RNA, which makes it a promising tool for RNA detection. The protein uses a CRISPR RNA (crRNA) to target RNA sequences, which are cleaved by a composite active site formed by two 'Higher Eukaryotes and Prokaryotes Nucleotide' (HEPN) catalytic domains. In this system, an intriguing form of allosteric communication controls RNA cleavage activity, yet its molecular details are unknown. Here, multiple-microsecond molecular dynamics simulations are combined with graph theory and RNA cleavage assays to decipher this activation mechanism. We show that the binding of a target RNA acts as an allosteric effector of the spatially distant HEPN catalytic cleft, by amplifying the allosteric signals over the dynamical noise, that passes through the buried HEPN interface. Critical residues in this region - N378, R973, and R377 - rearrange their interactions upon target RNA binding, and alter allosteric signalling. Alanine mutation of these residues is experimentally shown to select target RNA over an extended complementary sequence beyond guide-target duplex, for RNA cleavage. Altogether, our findings offer a fundamental understanding of the Cas13a mechanism of action and pave new avenues for the development of more selective RNA-based cleavage and detection tools.

New design strategies for ultra-specific CRISPR-Cas13a-based RNA-diagnostic tools with single-nucleotide mismatch sensitivity.

The pressing need for clinical diagnostics has required the development of novel nucleic acid-based detection technologies that are sensitive, fast, and inexpensive, and that can be deployed at point-of-care. Recently, the RNA-guided ribonuclease CRISPR-Cas13 has been successfully harnessed for such purposes. However, developing assays for detection of genetic variability, for example single-nucleotide polymorphisms, is still challenging and previously described design strategies are not always generalizable. Here, we expanded our characterization of LbuCas13a RNA-detection specificity by performing a combination of experimental RNA mismatch tolerance profiling, molecular dynamics simulations, protein, and crRNA engineering. We found certain positions in the crRNA-target-RNA duplex that are particularly sensitive to mismatches and establish the effect of RNA concentration in mismatch tolerance. Additionally, we determined that shortening the crRNA spacer or modifying the direct repeat of the crRNA leads to stricter specificities. Furthermore, we harnessed our understanding of LbuCas13a allosteric activation pathways through molecular dynamics and structure-guided engineering to develop novel Cas13a variants that display increased sensitivities to single-nucleotide mismatches. We deployed these Cas13a variants and crRNA design strategies to achieve superior discrimination of SARS-CoV-2 strains compared to wild-type LbuCas13a. Together, our work provides new design criteria and new Cas13a variants for easier-to-implement Cas13-based diagnostics. KEY POINTS: Certain positions in the Cas13a crRNA-target-RNA duplex are particularly sensitive to mismatches.Understanding Cas13a's allosteric activation pathway allowed us to develop novel high-fidelity Cas13a variants.These Cas13a variants and crRNA design strategies achieve superior discrimination of SARS-CoV-2 strains.

Machines on Genes through the Computational Microscope.

Macromolecular machines acting on genes are at the core of life's fundamental processes, including DNA replication and repair, gene transcription and regulation, chromatin packaging, RNA splicing, and genome editing. Here, we report the increasing role of computational biophysics in characterizing the mechanisms of "machines on genes", focusing on innovative applications of computational methods and their integration with structural and biophysical experiments. We showcase how state-of-the-art computational methods, including classical and ab initio molecular dynamics to enhanced sampling techniques, and coarse-grained approaches are used for understanding and exploring gene machines for real-world applications. As this review unfolds, advanced computational methods describe the biophysical function that is unseen through experimental techniques, accomplishing the power of the "computational microscope", an expression coined by Klaus Schulten to highlight the extraordinary capability of computer simulations. Pushing the frontiers of computational biophysics toward a pragmatic representation of large multimegadalton biomolecular complexes is instrumental in bridging the gap between experimentally obtained macroscopic observables and the molecular principles playing at the microscopic level. This understanding will help harness molecular machines for medical, pharmaceutical, and biotechnological purposes.

GPU-Enhanced DFTB Metadynamics for Efficiently Predicting Free Energies of Biochemical Systems.

Metadynamics calculations of large chemical systems with ab initio methods are computationally prohibitive due to the extensive sampling required to simulate the large degrees of freedom in these systems. To address this computational bottleneck, we utilized a GPU-enhanced density functional tight binding (DFTB) approach on a massively parallelized cloud computing platform to efficiently calculate the thermodynamics and metadynamics of biochemical systems. To first validate our approach, we calculated the free-energy surfaces of alanine dipeptide and showed that our GPU-enhanced DFTB calculations qualitatively agree with computationally-intensive hybrid DFT benchmarks, whereas classical force fields give significant errors. Most importantly, we show that our GPU-accelerated DFTB calculations are significantly faster than previous approaches by up to two orders of magnitude. To further extend our GPU-enhanced DFTB approach, we also carried out a 10 ns metadynamics simulation of remdesivir, which is prohibitively out of reach for routine DFT-based metadynamics calculations. We find that the free-energy surfaces of remdesivir obtained from DFTB and classical force fields differ significantly, where the latter overestimates the internal energy contribution of high free-energy states. Taken together, our benchmark tests, analyses, and extensions to large biochemical systems highlight the use of GPU-enhanced DFTB simulations for efficiently predicting the free-energy surfaces/thermodynamics of large biochemical systems.

Structural basis for Cas9 off-target activity.

The target DNA specificity of the CRISPR-associated genome editor nuclease Cas9 is determined by complementarity to a 20-nucleotide segment in its guide RNA. However, Cas9 can bind and cleave partially complementary off-target sequences, which raises safety concerns for its use in clinical applications. Here, we report crystallographic structures of Cas9 bound to bona fide off-target substrates, revealing that off-target binding is enabled by a range of noncanonical base-pairing interactions within the guide:off-target heteroduplex. Off-target substrates containing single-nucleotide deletions relative to the guide RNA are accommodated by base skipping or multiple noncanonical base pairs rather than RNA bulge formation. Finally, PAM-distal mismatches result in duplex unpairing and induce a conformational change in the Cas9 REC lobe that perturbs its conformational activation. Together, these insights provide a structural rationale for the off-target activity of Cas9 and contribute to the improved rational design of guide RNAs and off-target prediction algorithms.

Enhancement of CRISPR/Cas12a trans-cleavage activity using hairpin DNA reporters.

The RNA programmed non-specific (trans) nuclease activity of CRISPR-Cas Type V and VI systems has opened a new era in the field of nucleic acid-based detection. Here, we report on the enhancement of trans-cleavage activity of Cas12a enzymes using hairpin DNA sequences as FRET-based reporters. We discover faster rate of trans-cleavage activity of Cas12a due to its improved affinity (Km) for hairpin DNA structures, and provide mechanistic insights of our findings through Molecular Dynamics simulations. Using hairpin DNA probes we significantly enhance FRET-based signal transduction compared to the widely used linear single stranded DNA reporters. Our signal transduction enables faster detection of clinically relevant double stranded DNA targets with improved sensitivity and specificity either in the presence or in the absence of an upstream pre-amplification step.

Dynamics and mechanisms of CRISPR-Cas9 through the lens of computational methods.

The clustered regularly interspaced short palindromic repeat (CRISPR) genome-editing revolution established the beginning of a new era in life sciences. Here, we review the role of state-of-the-art computations in the CRISPR-Cas9 revolution, from the early refinement of cryo-EM data to enhanced simulations of large-scale conformational transitions. Molecular simulations reported a mechanism for RNA binding and the formation of a catalytically competent Cas9 enzyme, in agreement with subsequent structural studies. Inspired by single-molecule experiments, molecular dynamics offered a rationale for the onset of off-target effects, while graph theory unveiled the allosteric regulation. Finally, the use of a mixed quantum-classical approach established the catalytic mechanism of DNA cleavage. Overall, molecular simulations have been instrumental in understanding the dynamics and mechanism of CRISPR-Cas9, contributing to understanding function, catalysis, allostery, and specificity.

Structural Basis for Reduced Dynamics of Three Engineered HNH Endonuclease Lys-to-Ala Mutants for the Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-Associated 9 (CRISPR/Cas9) Enzyme.

Many bacteria possess type-II immunity against invading phages or plasmids known as the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated 9 (Cas9) system to detect and degrade the foreign DNA sequences. The Cas9 protein has two endonucleases responsible for double-strand breaks (the HNH domain for cleaving the target strand of DNA duplexes and RuvC domain for the nontarget strand, respectively) and a single-guide RNA-binding domain where the RNA and target DNA strands are base-paired. Three engineered single Lys-to-Ala HNH mutants (K810A, K848A, and K855A) exhibit an enhanced substrate specificity for cleavage of the target DNA strand. We report in this study that in the wild-type (wt) enzyme, D835, Y836, and D837 within the Y836-containing loop (comprising E827-D837) adjacent to the catalytic site have uncharacterizable broadened 1H15N nuclear magnetic resonance (NMR) features, whereas remaining residues in the loop have different extents of broadened NMR spectra. We find that this loop in the wt enzyme exhibits three distinct conformations over the duration of the molecular dynamics simulations, whereas the three Lys-to-Ala mutants retain only one conformation. The versatility of multiple alternate conformations of this loop in the wt enzyme could help to recruit noncognate DNA substrates into the HNH active site for cleavage, thereby reducing its substrate specificity relative to the three mutants. Our study provides further experimental and computational evidence that Lys-to-Ala substitutions reduce dynamics of proteins and thus increase their stability.

Emerging Methods and Applications to Decrypt Allostery in Proteins and Nucleic Acids.

Many large protein-nucleic acid complexes exhibit allosteric regulation. In these systems, the propagation of the allosteric signaling is strongly coupled to conformational dynamics and catalytic function, challenging state-of-the-art analytical methods. Here, we review established and innovative approaches used to elucidate allosteric mechanisms in these complexes. Specifically, we report network models derived from graph theory and centrality analyses in combination with molecular dynamics (MD) simulations, introducing novel schemes that implement the synergistic use of graph theory with enhanced simulations methods and ab-initio MD. Accelerated MD simulations are used to construct "enhanced network models", describing the allosteric response over long timescales and capturing the relation between allostery and conformational changes. "Ab-initio network models" combine graph theory with ab-initio MD and quantum mechanics/molecular mechanics (QM/MM) simulations to describe the allosteric regulation of catalysis by following the step-by-step dynamics of biochemical reactions. This approach characterizes how the allosteric regulation changes from reactants to products and how it affects the transition state, revealing a tense-to-relaxed allosteric regulation along the chemical step. Allosteric models and applications are showcased for three paradigmatic examples of allostery in protein-nucleic acid complexes: (i) the nucleosome core particle, (ii) the CRISPR-Cas9 genome editing system and (iii) the spliceosome. These methods and applications create innovative protocols to determine allosteric mechanisms in protein-nucleic acid complexes that show tremendous promise for medicine and bioengineering.

Principles of target DNA cleavage and the role of Mg2+ in the catalysis of CRISPR-Cas9.

At the core of the CRISPR-Cas9 genome-editing technology, the endonuclease Cas9 introduces site-specific breaks in DNA. However, precise mechanistic information to ameliorating Cas9 function is still missing. Here, multi-microsecond molecular dynamics, free-energy and multiscale simulations are combined with solution NMR and DNA cleavage experiments to resolve the catalytic mechanism of target DNA cleavage. We show that the conformation of an active HNH nuclease is tightly dependent on the catalytic Mg2+, unveiling its cardinal structural role. This activated Mg2+-bound HNH is consistently described through molecular simulations, solution NMR and DNA cleavage assays, revealing also that the protonation state of the catalytic H840 is strongly affected by active site mutations. Finally, ab-initio QM(DFT)/MM simulations and metadynamics establish the catalytic mechanism, showing that the catalysis is activated by H840 and completed by K866, rationalising DNA cleavage experiments. This information is critical to enhance the enzymatic function of CRISPR-Cas9 toward improved genome-editing.

Twisting and swiveling domain motions in Cas9 to recognize target DNA duplexes, make double-strand breaks, and release cleaved duplexes.

The CRISPR-associated protein 9 (Cas9) has been engineered as a precise gene editing tool to make double-strand breaks. CRISPR-associated protein 9 binds the folded guide RNA (gRNA) that serves as a binding scaffold to guide it to the target DNA duplex via a RecA-like strand-displacement mechanism but without ATP binding or hydrolysis. The target search begins with the protospacer adjacent motif or PAM-interacting domain, recognizing it at the major groove of the duplex and melting its downstream duplex where an RNA-DNA heteroduplex is formed at nanomolar affinity. The rate-limiting step is the formation of an R-loop structure where the HNH domain inserts between the target heteroduplex and the displaced non-target DNA strand. Once the R-loop structure is formed, the non-target strand is rapidly cleaved by RuvC and ejected from the active site. This event is immediately followed by cleavage of the target DNA strand by the HNH domain and product release. Within CRISPR-associated protein 9, the HNH domain is inserted into the RuvC domain near the RuvC active site via two linker loops that provide allosteric communication between the two active sites. Due to the high flexibility of these loops and active sites, biophysical techniques have been instrumental in characterizing the dynamics and mechanism of the CRISPR-associated protein 9 nucleases, aiding structural studies in the visualization of the complete active sites and relevant linker structures. Here, we review biochemical, structural, and biophysical studies on the underlying mechanism with emphasis on how CRISPR-associated protein 9 selects the target DNA duplex and rejects non-target sequences.

Structural and dynamic insights into the HNH nuclease of divergent Cas9 species.

CRISPR-Cas9 is a widely used biochemical tool with applications in molecular biology and precision medicine. The RNA-guided Cas9 protein uses its HNH endonuclease domain to cleave the DNA strand complementary to its endogenous guide RNA. In this study, novel constructs of HNH from two divergent organisms, G. stearothermophilus (GeoHNH) and S. pyogenes (SpHNH) were engineered from their respective full-length Cas9 proteins. Despite low sequence similarity, the X-ray crystal structures of these constructs reveal that the core of HNH surrounding the active site is conserved. Structure prediction of the full-length GeoCas9 protein using Phyre2 and AlphaFold2 also showed that the crystallographic construct of GeoHNH represents the structure of the domain within the full-length GeoCas9 protein. However, significant differences are observed in the solution dynamics of structurally conserved regions of GeoHNH and SpHNH, the latter of which was shown to use such molecular motions to propagate the DNA cleavage signal. Indeed, molecular simulations show that the intradomain signaling pathways, which drive SpHNH function, are non-specific and poorly formed in GeoHNH. Taken together, these outcomes suggest mechanistic differences between mesophilic and thermophilic Cas9 species.

Enhanced specificity mutations perturb allosteric signaling in CRISPR-Cas9.

CRISPR-Cas9 (clustered regularly interspaced short palindromic repeat and associated Cas9 protein) is a molecular tool with transformative genome editing capabilities. At the molecular level, an intricate allosteric signaling is critical for DNA cleavage, but its role in the specificity enhancement of the Cas9 endonuclease is poorly understood. Here, multi-microsecond molecular dynamics is combined with solution NMR and graph theory-derived models to probe the allosteric role of key specificity-enhancing mutations. We show that mutations responsible for increasing the specificity of Cas9 alter the allosteric structure of the catalytic HNH domain, impacting the signal transmission from the DNA recognition region to the catalytic sites for cleavage. Specifically, the K855A mutation strongly disrupts the allosteric connectivity of the HNH domain, exerting the highest perturbation on the signaling transfer, while K810A and K848A result in more moderate effects on the allosteric communication. This differential perturbation of the allosteric signal correlates to the order of specificity enhancement (K855A > K848A ~ K810A) observed in biochemical studies, with the mutation achieving the highest specificity most strongly perturbing the signaling transfer. These findings suggest that alterations of the allosteric communication from DNA recognition to cleavage are critical to increasing the specificity of Cas9 and that allosteric hotspots can be targeted through mutational studies for improving the system's function.

Gaussian accelerated molecular dynamics (GaMD): principles and applications.

Gaussian accelerated molecular dynamics (GaMD) is a robust computational method for simultaneous unconstrained enhanced sampling and free energy calculations of biomolecules. It works by adding a harmonic boost potential to smooth biomolecular potential energy surface and reduce energy barriers. GaMD greatly accelerates biomolecular simulations by orders of magnitude. Without the need to set predefined reaction coordinates or collective variables, GaMD provides unconstrained enhanced sampling and is advantageous for simulating complex biological processes. The GaMD boost potential exhibits a Gaussian distribution, thereby allowing for energetic reweighting via cumulant expansion to the second order (i.e., "Gaussian approximation"). This leads to accurate reconstruction of free energy landscapes of biomolecules. Hybrid schemes with other enhanced sampling methods, such as the replica exchange GaMD (rex-GaMD) and replica exchange umbrella sampling GaMD (GaREUS), have also been introduced, further improving sampling and free energy calculations. Recently, new "selective GaMD" algorithms including the ligand GaMD (LiGaMD) and peptide GaMD (Pep-GaMD) enabled microsecond simulations to capture repetitive dissociation and binding of small-molecule ligands and highly flexible peptides. The simulations then allowed highly efficient quantitative characterization of the ligand/peptide binding thermodynamics and kinetics. Taken together, GaMD and its innovative variants are applicable to simulate a wide variety of biomolecular dynamics, including protein folding, conformational changes and allostery, ligand binding, peptide binding, protein-protein/nucleic acid/carbohydrate interactions, and carbohydrate/nucleic acid interactions. In this review, we present principles of the GaMD algorithms and recent applications in biomolecular simulations and drug design.

Making it Rain: Cloud-Based Molecular Simulations for Everyone.

We present a user-friendly front-end for running molecular dynamics (MD) simulations using the OpenMM toolkit on the Google Colab framework. Our goals are (1) to highlight the usage of a cloud-computing scheme for educational purposes for a hands-on approach when learning MD simulations and (2) to exemplify how low-income research groups can perform MD simulations in the microsecond time scale. We hope this work facilitates teaching and learning of molecular simulation throughout the community.

Role of Electrostatic Hotspots in the Selectivity of Complement Control Proteins Toward Human and Bovine Complement Inhibition.

Poxviruses are dangerous pathogens, which can cause fatal infection in unvaccinated individuals. The causative agent of smallpox in humans, variola virus, is closely related to the bovine vaccinia virus, yet the molecular basis of their selectivity is currently incompletely understood. Here, we examine the role of the electrostatics in the selectivity of the smallpox protein SPICE and vaccinia protein VCP toward the human and bovine complement protein C3b, a key component of the complement immune response. Electrostatic calculations, in-silico alanine-scan and electrostatic hotspot analysis, as introduced by Kieslich and Morikis (PLoS Comput. Biol. 2012), are used to assess the electrostatic complementarity and to identify sites resistant to local perturbation where the electrostatic potential is likely to be evolutionary conserved. The calculations suggest that the bovine C3b is electrostatically prone to selectively bind its VCP ligand. On the other hand, the human isoform of C3b exhibits a lower electrostatic complementarity toward its SPICE ligand. Yet, the human C3b displays a highly preserved electrostatic core, which suggests that this isoform could be less selective in binding different ligands like SPICE and the human Factor H. This is supported by experimental cofactor activity assays revealing that the human C3b is prone to bind both SPICE and Factor H, which exhibit diverse electrostatic properties. Additional investigations considering mutants of SPICE and VCP that revert their selectivity reveal an "electrostatic switch" into the central modules of the ligands, supporting the critical role of the electrostatics in the selectivity. Taken together, these evidences provide insights into the selectivity mechanism of the complement regulator proteins encoded by the variola and vaccinia viruses to circumvent the complement immunity and exert their pathogenic action. These fundamental aspects are valuable for the development of novel vaccines and therapeutic strategies.