Human T lymphotropic virus-1 (HTLV-1) was the first identified oncoretrovirus, which infects and establishes a persistent infection in approximately 10–20 million people worldwide. Although only ~5% of infected individuals develop pathologies such as adult T-cell leukemia/lymphoma (ATLL) or a neuroinflammatory disorder termed HTLV-1-asssociated myelopathy/tropical spastic paraparesis (HAM/TSP), asymptomatic carriers are more susceptible to opportunistic infections. Furthermore, ATLL patients are severely immunosuppressed and prone to other malignancies and other infections. The HTLV-1 replication cycle provides ligands, mainly nucleic acids , that are sensed by different pattern recognition receptors (PRRs) to trigger immune responses. However, the mechanisms of innate immune detection and immune responses to HTLV-1 infection are not well understood. In this review, we highlight the functional roles of different immune sensors in recognizing HTLV-1 infection in multiple cell types and the antiviral roles of host restriction factors in limiting persistent infection of HTLV-1. We also provide a comprehensive overview of intricate strategies employed by HTLV-1 to subvert the host innate immune response that may contribute to the development of HTLV-1-associated diseases. A more detailed understanding of HTLV-1-host pathogen interactions may inform novel strategies for HTLV-1 antivirals, vaccines, and treatments for ATLL or HAM/TSP. The human T lymphotropic virus type 1 (HTLV-1) was discovered as the first human oncogenic retrovirus and belongs to the family Retroviridae and genus Deltaretrovirus . HTLV-1 HTLV-1 is a highly oncogenic virus with regulatory proteins that can modulate host cellular signaling pathways and cell cycle checkpoints to enhance the clonal proliferation and long-term persistence of infected cells that can eventually lead to leukemia/lymphoma. In addition, HTLV-1 evades immune surveillance through limiting its replication via tight control of viral gene expression. Although HTLV-1 was discovered more than 40 years ago, the innate immune responses generated during the different stages of HTLV-1 infection remain poorly understood, likely due to the lack of a tractable infection model and unique infection mechanisms utilized by HTLV-1. However, there is accumulating research evidence describing immune escape strategies employed by HTLV-1 to counteract the host immune surveillance in infected individuals. In this review, we will discuss the current knowledge of innate immune sensing of HTLV-1 and the restriction factors involved to counteract viral replication at multiple levels. Additionally, this review also discusses the HTLV-1-mediated immune evasion strategies to prevent recognition and destruction of infected cells by the innate immune system.HTLV-1 is a spherical enveloped virus approximately 100 nm in diameter and contains linear, dimeric positive-sense and single-strand genomic RNA inside an envelope embedded with protruding viral glycoproteins (gp46 and gp21) . The icoThe life cycle of HTLV-1 is analogous to other retroviruses; however, HTLV-1 cell-free virions are poorly infectious, and cell-to-cell spread between infected cells and target cells via the virological synapse is crucial for the transmission of the virus ,16. The Pathogen recognition receptors (PRRs) recognize pathogen-associated molecular patterns (PAMPs) in viruses, typically nucleic acids, to trigger an immune response through the secretion of type I IFN and proinflammatory cytokines . PRRs arTLR3 is widely expressed in the endosomal compartment of innate immune cells and recognizes retroviral double-stranded RNA, a viral replication intermediate, to trigger antiviral activities through secreting IFNs and inflammatory cytokines . Single The immune response triggered by professional ‘sentinel’ or plasmacytoid dendritic cells (pDCs) is largely induced through TLR7- or TLR9-mediated recognition of RNA from retroviruses ,35. ColiIFI16 is a critical intracellular DNA sensor that interacts with dsDNA through direct binding and is characterized as an IFN-inducible protein in antiviral immune responses . IFI16 iSTING is an ER-localized adaptor that plays a critical role in the cGAS DNA sensing pathway. cGAS senses viral or host dsDNAs and generates the cyclic dinucleotide 2′3′-cGAMP (cyclic GMP-AMP) that binds to and activates STING. STING then traffics to the Golgi where it recruits TBK1 for downstream activation of IRF3 and NF-κB to induce type I IFNs and proinflammatory cytokines to limit viral replication ,49. STINKu70 is well studied for its crucial role in the dsDNA break repair pathway through non-homologous end joining in a complex with Ku80 and the catalytic subunit DNA-PKcs ,52. ReceInnate and adaptive immunity cooperate in multiple ways to counteract viral infection. In addition, several host intrinsic cellular proteins termed restriction factors (RFs) contribute to the frontline defense to impede viral infections. Restriction factors are either constitutively expressed or induced by mediators of innate immunity such as type I IFN (interferon-stimulated genes or ISGs) to recognize and inhibit viral replication at multiple steps of the viral infection cycle, in a cell-autonomous manner ,62. RFs Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) catalyzes the deamination of cytidine to uridine in single-stranded DNA substrates resulting in G-to-A mutations . APOBEC3Although HTLV-1 predominantly infects T-cells, myeloid cells are also potential targets of HTLV-1 infection ,76,77. TTetherin, also known as bone marrow stromal cell antigen 2 or BST-2, functions as a restriction factor through inhibiting the release of viral particles from infected cells; however, HIV-1 Vpu antagonizes the action of tetherin in retaining viral particles at the cell surface through depleting its expression ,83,84. IThe MHC class II transcriptional activator (CIITA) plays a critical role in triggering adaptive immune responses through efficient control of antigen presentation to CD4+ helper (TH) cells and can also initiate direct antiviral activity through inhibiting viral expression in a cell-autonomous manner ,87. CIITThe CCCH-type zinc finger antiviral protein, also known as ZAP, successfully restricts retroviral infections such as HIV-1, murine leukemia virus (MLV), and avian leukosis virus (ALV) as well as several other viruses including Hepatitis B virus, influenza A virus, and flaviviruses ,94,95,96The tripartite motif (TRIM) family comprises several interferon-induced proteins that carry out key roles in restricting viral infections . TRIM5α Another TRIM family member, TRIM19 ), also functions as a restriction factor against HTLV-1 infection . NuclearAdenosine deaminase acting on RNA (ADAR) is a cellular RNA-editing protein involved in post-transcriptional processing of dsRNA and comprises three members: ADAR1, ADAR2, and ADAR3 . Type I Micro RNAs (miRNAs) can also act as restriction factors to defend against retroviral infections, and recent studies have highlighted the importance of certain miRNAs in HTLV-1-associated disease pathogenesis ,114,115.Innate immune-mediated inflammation plays a critical role in inhibiting pathogenic viruses. Innate immune receptors trigger the production of pro-inflammatory cytokines and interferons (IFNs), as well as signals that recruit and activate cells that orchestrate inflammation and the induction of adaptive immunity. Likewise, cellular immune responses have been implicated in the control of HTLV-1 infection as well as the development of inflammatory disorders in patients . MembersAlthough the induction of innate immunity and inflammation in response to viral infection is important to control virus replication, several oncogenic viruses, including HTLV-1, modulate inflammatory effector molecules that promote an environment conducive to cancer development. Mounting evidence suggests that acute inflammation is mostly associated with an antipathogenic role, whereas chronic inflammation favors cancer development . MoreoveHTLV-1 infection triggers the stimulation of multiple PRRs and activation of immune pathways and ISGs to counteract viral infection at multiple steps during the HTLV-1 replication cycle. To establish successful infection, replication, and persistence, HTLV-1 employs numerous immune evasion strategies to counteract innate immune responses targeting the virus. HTLV-1 targets and manipulates different immune sensors, restriction factors, transcription factors, and downstream signaling cascades for IFN production. These immune escape mechanisms disrupt antiviral immune signaling to prevent host-mediated viral clearance and facilitate HTLV-1 persistence and potential development of HTLV-1-associated pathogenesis. Understanding the underlying immune escape mechanisms of HTLV-1 is essential to design and develop novel antiviral therapeutics. Below, we have highlighted known strategies utilized by HTLV-1 to evade host antiviral defense programs .The pX region of the HTLV-1 genome encodes a regulatory protein Tax which acts as a transcriptional activator that promotes viral gene expression through the recruitment of cellular transcription factors such as CREB and CBP/p300 to the viral 5′ LTR promoter . Tax is Intriguingly, Tax interacts with and inhibits the adaptor TIR-domain-containing adapter-inducing interferon-β (TRIF), likely to impair endosomal sensing of dsRNA through TLR3 signaling and downstream innate immune signaling . MoreoveThe cGAS-STING pathway recognizes dsDNA and triggers innate immune responses through IRF3-mediated IFN-β production. HTLV-1 circumvents the antiviral action of type I IFN through Tax-driven suppression of IRF3 activity . Tax intIFNs trigger ISG expression through Janus kinase (JAK)-dependent phosphorylation of signal transducer and activator of transcription (STAT) 1 and STAT2 to amplify IFN-mediated antiviral immune responses and block viral replication at multiple steps. Tax prevents IFN-induced JAK-STAT signaling through competing with STAT2 for CBP/p300 coactivators . MoreoveThe minus strand of the HTLV-1 provirus encodes a bZIP (basic leucine zipper factor) nuclear factor, termed HBZ. Unlike Tax, HBZ is steadily expressed at low levels in vivo because of an intact 3′ LTR and the absence of abortive epigenetic or genetic changes; HBZ promotes the persistent proliferation of HTLV-1-infected T-cells . InteresThe HTLV-1 doubly spliced mRNA containing open reading frame II (orf-II) encodes a nuclear/nucleolar protein, p30, with both transcriptional and post-transcriptional activity. The p30 protein attenuates active HTLV-1 replication and promotes viral latency through retaining the doubly spliced mRNA encoding Tax and Rex proteins in the nucleus and disrupting the CREB-Tax-p300 complex essential for 5′ LTR activation ,177. HTLHTLV-1 open reading frame I (orf-I) encodes a small hydrophobic protein, p12, which can be further processed into p8 through proteolytic cleavage. p12/p8 are not essential for HTLV-1 replication and transformation of infected cells; however, the binding of p12/p8 to IL-2R results in increased phosphorylation of STAT5 that allows T-cell proliferation in the absence of IL-2 and with suboptimal antigen stimulation, thus providing a growth advantage for HTLV-1-infected T-cells . p12 is HTLV-1 infection is prevalent in different parts of the world with increasing spread of HTLV-1 to non-endemic areas. Although a minority of infected individuals develop HTLV-1-associated diseases later in life, immunosuppression commonly occurs in ATLL which allows for opportunistic infections. There is clearly an unmet need for effective HTLV-1 vaccines, antivirals, and novel therapeutic approaches for ATLL and HAM/TSP. The major obstacle in designing vaccines and effective antivirals stems from an inadequate understanding of the early events of HTLV-1 infection and the host response to infection. Additionally, immune evasion strategies of HTLV-1 and its interactions with the innate immune system are not well understood. Interestingly, HTLV-1 does not express any specific proteins dedicated for immune evasion seen with other retroviruses; also, the functional roles of HTLV-1-encoded proteins in immune modulation only are partially explored. Thus, further studies focusing on the role of HTLV-1-encoded structural proteins along with regulatory or accessory proteins may provide novel therapeutic targets for viral intervention. Of note, targeting molecular events to counteract host-mediated antiviral immunity during the progression from asymptomatic infection to ATLL or HAM/TSP may provide promising strategies to develop novel antivirals against HTLV-1 infection. Several innate immune sensors have been reported to interact with HTLV-1 RNA or DNA at multiple stages of the viral life cycle in different cell types. Interestingly, HTLV-1 infection in vitro involves broad tropism with restricted viral replication in certain cell types in vivo, thus raising the possibility of specific restriction factors or immune mediators triggering IFN production for the prevention of productive replication to generate mature virions. Likewise, cell types susceptible to HTLV-1 infection display minimal or undetectable IFN levels, implying successful immune evasion by HTLV-1 to induce clonal proliferation for long-term persistence. Restriction factors with antiviral action against HTLV-1 are very limited as the majority of investigations are inspired by the HIV field. However, the structural and functional similarity of Tax with foamy virus transactivator protein, Tas, may be instructive in discovering new restriction factors such as TRIM28 and Pirh2 that restrict foamy virus replication through proteasomal degradation of Tas ,193. TheIn conclusion, increased mechanistic insight into HTLV-1-triggered immune responses during early infection and the corresponding viral immune evasion strategies may inform new approaches to modulate antiviral innate pathways and restrict the proviral load and possibly prevent HTLV-1-associated diseases.


Center of pressure (COP) tracking during posture transition is an ideal scale for determining the recurrence of an ankle injury, thereby preventing chronic ankle instability (CAI). However, the same is difficult to determine because the reduced ability of certain patients (who experienced sprain) to control posture at the ankle joint is masked by the chain of hip and ankle joint motion. Thus, we observed the effects of knee joint immobilization/non-immobilization on postural control strategies during the posture transition task and attempted to evaluate the detailed pathophysiology of CAI. Ten athletes with unilateral CAI were selected. To examine differences in COP trajectories in the CAI side and non-CAI legs, patients stood on both legs for 10 s and one leg for 20 s with/without knee braces. COP acceleration during the transition was significantly higher in the CAI group with a knee brace. The COP transition from the double- to single-leg stance phase was significantly longer in the CAI foot. In the CAI group, the fixation of the knee joint increased COP acceleration during postural deviation. This suggests that there is likely an ankle joint dysfunction in the CAI group that is masked by the hip strategy. Lateral ankle sprain (LAS) is a prevalent musculoskeletal injury that occurs frequently during sports activities . This tyPostural control ability is defined as the ability to maintain, achieve, or regain a state of balance in any upright position . PreviouTherefore, it has been suggested that changes in COP need to be evaluated along with changes in movement strategies between body segments . We holdThe purpose of this research was to examine the impact of various positions on the assessment of postural control in individuals with ankle instability. It was suggested that in the SLS position with knee flexion, the loss of postural control ability at the ankle joint was difficult to observe as it was masked by the chain of hip and ankle joint motion. To overcome this limitation, the study evaluated postural control ability in the SLS position with the knee fixed in extension. The hypothesis was that hidden ankle instability would be captured more prominently in this position, which could serve as a screening indicator for identifying individuals at high risk of re-injury. By comparing the results from both positions, the study aimed to provide valuable insights into developing effective rehabilitation programs for ankle instability.Furthermore, several prior studies have utilized distinct subject groups for those with CAI and those with healthy ankles. However, postural control ability can vary significantly between individuals and is contingent upon factors, such as ankle joint range of motion and proprioceptive sensation . It is aThe purpose of this research was to investigate how the function of the knee joint affects the DLS-SLS test on the opposite side to the CAI in individuals who suffer from CAI in only one foot. The primary goal was to detect any ankle instability that might be hidden by the movement of the hip joint chain. Our hypothesis was that the CAI group, with their knee joint fixed in extension, would exhibit a more significant deviation in the center of pressure than the non-CAI group. This difference would indicate a concealed phenomenon that would remain undetected otherwise. By gaining a deeper understanding of the pathophysiology of CAI, we can develop more effective evaluation methods to identify individuals who are at a higher risk of re-injury from ankle sprains.From Niigata University of Health and Welfare, we surveyed 186 male students using the International Ankle Consortium guidelines to assess subjective ankle joint instability. Out of the total number of participants, 23 individuals (12.43%) were included in the CAI group based on the inclusion criteria. Moreover, 10 participants (43.2%) from the symptomatic group were found to have CAI in only one foot, based on the same criteria. The inclusion criteria were: (1) a score of 25 or less on the Cumberland Ankle Instability Tool (CAIT) (Japanese version) , a recomThe experimental task consists of the DLS-SLS test, which entails a 10 s barefoot double-leg standing phase followed by a 20 s single-leg standing phase, wherein the participant is required to maintain their heel alignment with respect to a reference line and keep their arms relaxed at their sides. During the practice test, a goniometer was used to measure the elevating leg to unify the flexion of 30 degrees at the hip joint and 45–50 degrees at the knee joint during the holding of the single-leg stand to improve reproducibility. The knee joint of the supporting leg was subjected to the following two conditions: (1) in the immobilized condition, the subject’s knee joint was immobilized with a knee brace  and held at 0 degrees of knee joint extension, and (2) the unfixed condition was performed under conditions that allowed the subject to bend the knee normally. More information regarding the experimental layout is provided in If any of the following occurred during the measurement—(1) the raised lower limb touched the floor, (2) the arms were unclasped, (3) holding time of single-leg standing position was less than 20 s—the trials were considered failed trials. COP deviations during the trial were measured at 300 Hz using a plantar pressure distribution measurement system (FootScan Entry Level Systems: Rsscan) that guaranteed accuracy and reliability .W) [D) and the width of the target area (W). The logarithm of this ratio is used to derive the travel difficulty index (ID) of the DLS-SLS transition. Additionally, we hypothesized that the increased amplitude of COP displacement at the target position would be regarded as a form of noise (N) in neuromuscular control, resulting in a higher ID value [In this study, we tried to verify the COP deviation and examine the area and movement acceleration. To analyze the DLS-SLS transition, we used Fitts’ model, which predicts that the time required to move to the region of a target that models human movement is a function of the distance to the target and its size. According to the assumptions underpinning Fitts’ model, achieving postural stability during the DLS-SLS transition necessitates moving the COP as expeditiously as feasible from its initial position to a target point located at a distance D with a width equal to that of the participant’s foot (W) . It is pID value .(1)ID=lp-value of <0.05 was considered significant.All statistical analyses were performed using R studio software. The difference between the subjective instability score and the time of the last ankle sprain was examined using a paired T-test. Regarding COP, the normality of distribution for quantitative data was assessed using the Kolmogorov–Smirnov test. In order to identify whether there were statistically significant differences between the feet (CAI vs. non-CAI) and the two conditions (baseline vs. knee brace), a repeated measures analysis of variance (ANOVA) was employed. A This study was conducted on male athletes who exercised regularly, with an average age of 20.5 ± 0.5 years. The mean body height of the participants was 180.1 + 1.5 cm, and their body weight was 83.0 ± 1.0 kg. The length and width of the participants’ feet were also measured, and the group means were calculated. The average foot length was 276.1 ± 10.4 mm, while the average width of the foot was 103.25 ± 6.1 mm. Out of the ten participants, six were diagnosed with certified CAI in their right foot, while the other four had it in their left foot. However, there were no significant differences in foot length and width between the two groups. This information indicates that any observed differences in the DLS-SLS test results were unlikely to be due to differences in foot dimensions.p < 0.05). The last ankle sprain according to the subjective injury history questionnaire was 3.0 ± 0.5 months on the CAI side and 18.0 ± 2.5 months on the non-CAI side, with a significant difference between the two groups (p < 0.01)  .The ML COP sway range  during tp < 0.01) (p < 0.05) (p < 0.05) (p < 0.05) (COP acceleration during the transition to SLS was significantly higher in the CAI group with knee brace than in the non-CAI group and the CAI group without knee brace ( < 0.01) . The dis < 0.05) . After t < 0.05) , and the < 0.05) , regardlp < 0.05).The difficulty index (ID) in the Fitts’ model can be estimated from the measurement of the player’s foot width (W) and the COP displacement distance (D) during the DLS-SLS transition (Equation (1)). Fitts’ model ID scores were 1.315 for the CAI group and 1.379 for the CAI group with knee braces, and 1.071 for the non-CAI group and 1.113 for the non-CAI group with knee braces. Fitts’ model ID was significantly higher in the CAI group than in the non-CAI group, both with and without the use of knee braces (The primary goal of the study was to assess how the COP transitions during DLS-SLS differed for individuals with CAI, with and without knee braces. Our aim was to investigate how knee braces impact postural stability control and to determine the role of the knee joint in this task. We compared the performance of participants with and without knee braces to gain insight into the effects of knee braces on the task. This study reduced the involvement of the kinetic chain between the lower extremity joints during the COP transitions from DLS to SLS. To evaluate the dynamic motor control ability more prominently at the ankle joint, a single-leg standing task was performed under two conditions: knee joint immobilization and non-immobilization. The kinetic chain was interrupted using knee braces, and only ankle function in the CAI group was assessed to look for indicators that could identify those most likely to re-injure. Furthermore, we are of the opinion that this verification process will provide us with a comprehensive understanding of the pathophysiology of CAI, and aid in the development of a post-onset CAI rehabilitation program.Considering the contribution of knee joint motion to standing postural control, the knee joint immobilization in the single-leg standing task used in this study reduces the degrees of freedom for motor control . This isThe CAI group significantly used the M-L range of COP during postural control in single-leg standing compared to the non-CAI group. This result may be due to the functional disruption of the ankle joint caused by the onset of CAI; abnormal joint position sense  and reduThe present study examined the effects of knee immobilization on postural control strategies in individuals with CAI during single-leg standing hold. The findings revealed that knee joint immobilization increased the contribution of hip control strategy, as demonstrated by the A-P strategy of COP. Specifically, the CAI group spent more time compensating for the M-L strategy, indicating a decreased reliance on the A-P strategy. The A-P strategy is known to increase the reliance on the hip joint strategy to maintain balance. Additionally, the results showed that knee immobilization unmasked previously undetected ankle joint dysfunctions in the CAI group, which were not apparent in other conditions. These findings are important since impaired balance ability increases the risk of re-injury from ankle sprains, and the CAI group’s heavy reliance on the hip joint strategy during postural control may result in delays during landing and cutting movements, leading to re-injury . TherefoThis study had several limitations. Firstly, the small sample size used in this study had a significant impact on the validity of the statistical interpretation of the results. Although individual differences in postural control ability were taken into account, the selection of subjects was limited to athletes with CAI in only one foot. Therefore, it is necessary to conduct a larger-scale study and collect a greater number of subjects in the future. Secondly, this study was a cross-sectional study and did not determine whether the CAI group had a higher re-injury rate than the non-CAI group. Thus, further validation, including prospective studies, may help to identify high-risk groups for ankle sprains based on the above points. Longitudinal studies can help to establish the causal relationship between the variables, whereas cross-sectional studies can only provide an overview of the situation. Thirdly, it is important to note that this study only included male subjects, and women were not included as subjects in this research. This is because the menstrual cycle is known to modulate ankle ligament laxity, and including women would have introduced additional confounding variables. To eliminate the various factors that can modulate laxity, only male subjects were included in this study. However, future studies should also include female subjects to ensure that the findings can be generalized to both genders. Finally, the assessment index did not take into account the subjects’ foot morphology and knee joint alignment, which could have had an impact on the results. Although preliminary validation was conducted because the effects of flatfoot and medial knee could not be eliminated, it was not feasible to incorporate these variables into the study due to difficulties in securing the subjects. Hence, future research should focus on conducting a detailed evaluation of foot morphology and knee joint alignment as determinants to obtain more accurate results. The inclusion of such variables may provide a more comprehensive understanding of the relationship between CAI and postural control ability.In this study, we aimed to explore the impact of knee immobilization and non-immobilization with knee brace on the postural control of CAI patients during postural transfer. The results of our study shed light on the changes in balance capacity caused by ankle instability by comparing postural control strategies under knee joint constraint conditions. Our findings revealed that ankle joint dysfunction, which may be masked by the hip joint strategy, was clearly evident in the knee immobilization condition. Moreover, using a knee brace for evaluation may uncover a more detailed pathophysiology of CAI. The CAI group exhibited increased COP acceleration during transfers, which suggests that they may use different strategies than the non-CAI group, putting them at higher risk of re-injuring the ankle. Based on our results, it can be inferred that the reliance of the CAI group on the hip joint strategy for postural control may cause delays in controlling their posture during landing and cutting movements, thereby increasing the risk of re-injury of the ankle sprain. Therefore, rehabilitation interventions aimed at improving balance function are of the utmost importance to enhance postural control ability that is specialized for the ankle joint strategy in CAI patients. This study also emphasizes the need for further research to identify new interventions that can improve postural control in patients with CAI.


Purkinje cell (PC) synapses onto cerebellar nuclei (CbN) neurons convey signals from the cerebellar cortex to the rest of the brain. PCs are inhibitory neurons that spontaneously fire at high rates, and many uniform sized PC inputs are thought to converge onto each CbN neuron to suppress or eliminate firing. Leading theories maintain that PCs encode information using either a rate code, or by synchrony and precise timing. Individual PCs are thought to have limited influence on CbN neuron firing. Here, we find that single PC to CbN synapses are highly variable in size, and using dynamic clamp and modelling we reveal that this has important implications for PC-CbN transmission. Individual PC inputs regulate both the rate and timing of CbN firing. Large PC inputs strongly influence CbN firing rates and transiently eliminate CbN firing for several milliseconds. Remarkably, the refractory period of PCs leads to a brief elevation of CbN firing prior to suppression. Thus, PC-CbN synapses are suited to concurrently convey rate codes, and generate precisely-timed responses in CbN neurons. Variable input sizes also elevate the baseline firing rates of CbN neurons by increasing the variability of the inhibitory conductance. Although this reduces the relative influence of PC synchrony on the firing rate of CbN neurons, synchrony can still have important consequences, because synchronizing even two large inputs can significantly increase CbN neuron firing. These findings may be generalized to other brain regions with highly variable sized synapses. The cerebellum is involved in behaviors ranging from balance, motor control and motor learning, to social and emotional behaviors . CerebelPCs are GABAergic and fire spontaneously at frequencies ranging from 10 spikes/s to over 100 spikes/s . It was PCs are thought to convey information either with a rate code, or with a synchrony/timing code . There iHere we reexamine how PCs control the firing of CbN neurons. Previously it was thought that PC-CbN synapses are uniformly small, and that single PC inputs have little influence on the firing of CbN neurons. However, we find that unitary PC-CbN inputs have highly variable amplitudes, and some are very large. We used dynamic clamp and simulations to explore the implications of nonuniform input sizes. We find that for a given total inhibitory conductance, nonuniform input sizes led to highly variable inhibitory conductances and high basal CbN firing rates. Inputs of all sizes regulated the rate and timing of CbN neuron firing, but larger inputs had a bigger influence. Although PC synchrony had less influence on the firing rates of CbN neurons for nonuniform sized inputs because of higher basal firing rates, synchronizing several large inputs effectively regulated the CbN neuron firing. Thus, the nonuniform distribution of PC input sizes has important implications for how firing rates, timing and synchrony convey signals from the cerebellar cortex to the CbN.upper, grey). The average of successes  and failures  are shown. This is also apparent in a plot of the IPSC amplitudes for each trial (lower) showing that the IPSCs were evoked in a fraction of the trials. Similar experiments are shown for a medium-sized input  and juvenile  animals . We cut ch trial , lower sed input , 1690 pAed input , 6280 pAed input , P10–20 ed input , P23–32 ed input , but in ed input . This ised input , and the− that provides superior voltage control to accurately determine the size of PC inputs. However, it has been shown in several studies that measurement of GABAR single-channel conductance or unitary conductance with high Cl− based internals will result in a 2–3 times bigger value . For simplicity, instead of having a continuous range of input sizes, we approximated the distribution of PC input sizes in juvenile animals . The timing and frequency of the inputs were based on PC firing recorded in awake-behaving mice, with each input firing at approximately 80 Hz (green), medium (blue), and large (red) conductances, which were then summed to generate the total inhibitory conductance arising from all inputs (black). The total inhibitory conductance showed large variations that were dominated by the medium and large inputs , while medium sized inputs strongly reduced CbN neuron spiking (middle), and large inputs transiently shut down CbN neurons for approximately 2 ms (right). Intriguingly, the inhibition generated by inhibitory inputs was preceded by an increase in spikes that was particularly prominent for large inputs (top) and inhibition (middle), as well as the duration of inhibition (bottom) were all positively correlated with the size of the PC input. These findings highlight the ability of large PC inputs to control the timing of CbN neuron spiking.All inputs had effects on the timing of CbN neuron firing, but larger inputs had much bigger effects. As shown in the cross-correlograms of input timing and CbN neuron spiking, small inputs produced a small transient decrease in CbN neuron spiking , left, w spiking , middle,ely 2 ms , right. e inputs . The mage inputs , top andhibition , middle,hibition , bottom red) until the total inhibitory conductance reached 200 nS. An example distribution of PC input sizes used in a simulation is shown in black), and for 9 other simulated neurons (grey). These simulations complemented our dynamic clamp studies and showed that the properties of cross-correlograms and their dependence on the size of the PC input can be extended to realistic distributions of input sizes.We then performed simulations to extend these findings to a more realistic distribution of PC inputs sizes . We dete neurons , grey. Tin vivo, it might be attributed to excitation of the CbN neuron that preceded PC inhibition, but that cannot be the case for our experimental conditions. Another possibility is that the refractory period of PC firing results in reduced inhibition and effective excitation. We tested this hypothesis by performing dynamic clamp experiments with the timing based on three different PCs recorded in vivo, and on an artificial Poisson distribution . Thus, the autocorrelations of PC firing led to elevated CbN firing prior to suppression.The elevated spiking observed prior to the inhibition by a PC input is intriguing. If such a cross-correlogram was observed ribution . As showribution  and autoribution , the thrductance , and conductance . The speductance . The Poiin vivo  of the inhibitory conductance influence CbN firing. We began by examining how changing the amplitude of a constant inhibitory conductance altered the firing of CbN neurons . The firin vivo ; Methodsin vivo , and thein vivo . Evoked in vivo  and 4f. in vivo . These fred) with different CVs and a total conductance value of 200 nS (solid lines), together with 40 uniform 5 nS PC inputs (dashed line), were used to generate inhibitory conductances for dynamic clamp experiments. Even though the average conductance was the same, the firing rates for the three nonuniform input sizes were higher than for uniform inputs  and decreased the CV (left) of the total inhibitory conductance, and suppressed the firing rate of CbN neurons (left). The CbN firing rate was inversely correlated with the firing rate of small inputs  and the inhibitory conductance amplitude , and positively correlated with the CV of the inhibitory conductance . Varying the firing rate of all medium inputs (middle) had qualitatively similar effects on the conductance (middle), the CV (middle), and the CbN firing rate , but had larger effects because of their larger contribution to the inhibitory conductance. Varying the firing frequency of all large inputs (right) affected the total conductance (right) similarly to varying the small and medium inputs but had a very different influence on the CV (right). Eliminating the firing of either the small or medium inputs increased the CV of the inhibitory conductance, whereas eliminating the firing of the large inputs decreased the CV of the inhibitory conductance (middle), but there were differences in the firing rate as a function of CV (right). These findings indicate that changes in the firing rate of PCs inputs are faithfully conveyed to the CbN primarily because of altering the total inhibitory conductance. Finally, to determine the influence of individual inputs on CbN firing, we calculated the slope of CbN output firing rate vs. the PC input firing rate for different size inputs and divided by the number of inputs , as in d the CV , left of neurons , left. Tm inputs , middle ductance , middle,, the CV , middle,te blue,, blue, be inputs , right aductance , right sn the CV , right. ductance . This isductance , or if tductance  is the pductance , middle,on of CV , right. f inputs . Comparef inputs . Therefoleft). Single large inputs were surprisingly effective at regulating the firing rates of CbN neurons. In this example, varying a single 37 nS input from 0 to 160 spikes/s decreased the output firing frequency from 126 spikes/s to 35 spikes/s (left). Similar to the dynamic clamp experiments, there was a remarkably consistent relationship between the firing rates of CbN neurons and the total PC input conductances (middle), which was not observed for the CbN firing rates vs CV of the total inhibitory conductance (right). Lastly, the slope of the CbN output firing rate/PC input firing rate was negatively correlated with the input size for the example neurons (black) and for 9 other neurons (grey). These simulations, along with the dynamic clamp studies, establish that individual PC inputs can regulate the firing rate of the CbN neuron, and that different sized inputs convey a rate code that depends on the amplitude of total inhibition.Simulations allowed us to examine the influences of individual PC inputs with a full range of sizes on the firing rates of CbN neurons. Simulations were similar to those of spikes/s , left. Suctances , middle,ductance , right.  neurons , black a neurons , grey. Tblack). The increases in CbN firing rate were 1.8-fold higher for 25% synchrony and 3.5-fold higher for 50% synchrony, respectively , increased the variability (left) and CV (left) of the conductance, which then elevated the firing of CbN neurons from 43 spikes/s to 91 spikes/s . Synchronizing 25% or 50% of either small or medium inputs barely increased the variability and CV of the conductance, and led to minimal increases in the firing of CbN neurons (right). These observations suggest that the effects of PC synchrony primarily depend on the total amplitude of synchronized inputs , the generated conductance was more variable , resultiiability , left an) and CV , left of/s left; . The fir/s left; , but bec/s left; . We also/s left; , right.  neurons –v, rightd inputs  and 6e. d inputs .black open circles). We also examined nonuniform sized inputs drawn from the full distribution of sizes (red), with a total conductance of 200 nS, and determined the firing rates evoked when we synchronized different combinations of inputs . The effects of synchrony on firing rates, and the dependence on the CV of the conductance were qualitatively similar for simulations (dark purple), but much less scatter when the firing rates were plotted as a function of the total amplitude of the synchronized inputs (dark purple). This is consistent with our observation that synchronizing many small or medium size inputs does not have much effect on the firing frequency of CbN neurons . 50% synchrony of uniform inputs silenced CbN neurons for several milliseconds, and this was proceeded by a prominent increase in CbN spiking (right). For asynchronous nonuniform inputs, as in left; red). Synchronizing 50% of all nonuniform inputs generated a cross-correlogram similar to that of synchronizing 50% uniform inputs (right). The strength of excitation (top), the amplitude of inhibition (bottom), and the duration of inhibition   , 1968. M0–50 Hz) .Our findings established that there is an inverse linear relationship between the firing rates of each PC input and the targeted CbN neuron  Person . The extPreviously it was also thought that an individual PC input has a small influence on the spike timing of a CbN neuron, and that it is necessary to synchronize the firing of many PCs to precisely entrain CbN firing . Our croSurprisingly, there was an excitatory response in CbN neuron firing preceding the suppression by PCs in the cross-correlogram of PC inputs and CbN neuron firing . This exin vivo, allow us to make several predictions about PC-CbN neuron cross-correlograms in vivo. It is expected that PCs to CbN synapses are sufficiently large that prominent suppression should be apparent in cross-correlograms in vivo. The variability of PC-CbN synapses amplitudes suggests that there will be considerable variability in the extent and duration of spike suppression that is comparable to The observed distribution of PC to CbN synapse amplitudes, combined with the firing properties of PCs in vivo  guidelines and protocols approved by the Harvard Medical Area Standing Committee on Animals.C57/BL6 wild-type mice (Charles River Laboratories) of both sexes aged P10 to P32 were used for acute slice experiments . All animal procedures were conducted in accordance with the National Institutes of Health and Animal Care and Use Committee guidelines and protocols approved by the Harvard Medical Area Standing Committee on Animals .2PO4, 25 NaHCO3, 25 glucose, 0.5 CaCl2, 7 MgCl2, 3.1 Na Pyruvate, 11.6 Na Ascorbate, 0.002 -CPP, 0.005 NBQX, oxygenated with 95% O2 / 5% CO2. To prepare sagittal cerebellar nuclei slices, the hindbrain was removed, a cut was made down the midline of the cerebellum and brainstem, and the halves of the cerebellum were glued down to the slicing chamber. Sagittal slices (170 μm) were cut using a Leica 1200S vibratome in warm choline ACSF (34°C). Slices were transferred to a holding chamber with warm ACSF solution (34°C) containing in mM: 127 NaCl, 2.5 KCl, 1.25 NaH2PO4, 25 NaHCO3, 25 glucose, 1.5 CaCl2, 1 MgCl2 and were recovered at 34°C for 10 minutes before being moved to room temperature for another 20–30 mins until recordings begin.Mice were anesthetized with ketamine / xylazine / acepromazine and transcardially perfused with warm choline ACSF solution (34°C) containing in mM: 110 Choline Cl, 2.5 KCl, 1.25 NaHWhole-cell voltage/current-clamp recordings were performed on large neurons (>70 pF) in the lateral and interposed deep cerebellar nuclei. These large cells are primarily glutamatergic projection neurons .Cl = 0 mV) internal containing in mM: 110 CsCl, 10 HEPES, 10 TEA-Cl, 1 MgCl2, 4 CaCl2, 5 EGTA, 20 Cs-BAPTA, 2 QX314, and 0.2 D600, adjusted to pH 7.3 with CsOH. BAPTA was included to prevent long-term plasticity  filled with ACSF was placed in the white matter between the CbN and the cerebellar cortex to activate PC axons. Minimal stimulation was used to determine the amplitudes of single PC-CbN inputs. The stimulus intensity was adjusted so that synaptic inputs were activated in approximately half the trials in a stochastic manner. The sample size was achieved by performing as many recordings as possible within a limited period of time.For voltage-clamp recordings of unitary PCs inputs to CbN neurons, Borosilicate glass electrodes (1–2 MΩ) were filled with a high chloride  were filled with an internal containing (in mM) 145 K-gluconate, 3 KCl, 5 HEPES, 5 HEPES-K, 0.5 EGTA, 3 Mg-ATP, 0.5 Na-GTP,5 phosphocreatine-tris2, and 5 phosphocreatine-Na2, adjusted to pH 7.2 with KOH. The osmolarity of internal solution was adjusted to 290–300 mOsm. Series resistances were less than 15 MΩ and were not compensated. Voltages were corrected for a liquid junction potential of 10 mV. Cells were held at −65 to −75 mV between trials. All experiments were performed at 34–35°C in the presence of 5 μM NBQX, 2.5 μM -CPP, 5 μM SR 95531 (Gabazine) and 1 μM strychnine to block most synaptic transmission.The total inhibitory conductance (200 nS) from all converging PCs in each CbN neurons was based on previous estimation of 40 PCs with a size of 5 nS (after depression) . Uniformred) until the total inhibitory conductance reached 200 nS. In experiments where the spike triggered averages were to be determined, we used a simplified distribution. In Dynamic clamp experiments with different size inputs were performed in in vivo recordings  EPSCs characterized in previous studies , with a To avoid a drastic increase in spike frequency and the following adaptation of CbN neurons resulting from big changes in the variability of conductances, we ramped up the CV of the inhibitory conductances in the beginning of each trial so that the firing rate of CbN increased gradually from the hyperpolarization state. Each conductance was repeated in the same neuron for 3–4 trials as technical replicates. For synchrony experiments, PC inputs were synchronized 100% in their spike times. Therefore, synchronizing 10 5 nS inputs is equivalent to having one big input with a size of 50 nS.Recordings were obtained using Multiclamp 700B (Molecular Devices), sampled at 50 kHz and filtered at 4 kHz, and collected in Igor Pro (WaveMetrics). Dynamic-clamp recordings were performed with an ITC-18 computer interface controlled by mafPC in Igor Pro (WaveMetrics). Data were analyzed using custom-written scripts in MATLAB (MathWorks) and Igor Pro (WaveMetrics). Auto-correlation and cross-correlation analysis were performed by generating accumulative histograms of spikes distribution within a 20 ms time window centering all spikes from the reference file , and normalized by the total spikes number of the reference file and the bin size of the histograms . All summary data are shown as the mean ± SEM unless otherwise indicated. The distributions of unitary PC input sizes in young and juvenile animals in https://github.com/asemptote/PC-DCN-different-size-inputs.Simulations were performed –j, o–p tIn red), along with 200 cells with varying numbers of uniform-size inputs such that the total conductance was 200 nS. Each cell was run for 10 s and the firing rates and inhibitory conductance CV were recorded. The generated conductance waves were saved for use in experiments in in vivo recording with a firing frequency of 100 Hz (In f 100 Hz .In In Supplement 1


This study takes a comprehensive approach to understand the dynamics of the cell-intrinsic response towards virus infection and how viruses actively modulate this. RIG-I recognizes viral dsRNA and activates a cell-autonomous antiviral response. Upon stimulation, it triggers a signaling cascade leading to the production of type I and III IFNs. IFNs are secreted and signal to elicit the expression of IFN-stimulated genes, establishing an antiviral state of the cell. The topology of this pathway has been studied intensively, however, its exact dynamics are less understood. Here, we employed electroporation to synchronously activate RIG-I, enabling us to characterize cell-intrinsic innate immune signaling at a high temporal resolution. Employing IFNAR1/IFNLR-deficient cells, we could differentiate primary RIG-I signaling from secondary signaling downstream of the IFN receptors. Based on these data, we developed a comprehensive mathematical model capable of simulating signaling downstream of dsRNA recognition by RIG-I and the feedback and signal amplification by IFN. We further investigated the impact of viral antagonists on signaling dynamics. Our work provides a comprehensive insight into the signaling events that occur early upon virus infection and opens new avenues to study and disentangle the complexity of the host–virus interface. Briefly, upon viral dsRNA recognition, RIG-I initiates a signaling cascade through mitochondrial antiviral-signaling protein (MAVS), leading to the activation and nuclear translocation of transcription factors such as IFN-regulatory factor 3 (IRF3) and NF-κB. Activation of these transcription factors results in the production and secretion of mostly type I and III IFNs. Auto- and paracrine IFN signaling through the corresponding IFN receptors (IFNR) can further induce multiple downstream signaling pathways. The most important signaling axis is the JAK/STAT pathway, leading to the formation of a transcription factor composed of the STAT of transcription 1 (STAT1), STAT2, and IRF9, in conjunction known as the ISGF3 complex. Upon activation, this complex binds to IFN-stimulated response elements within gene promoters, further leading to the induction of a large variety of ISGs, which exert numerous antiviral functions . In addiradation . Similarradation . Viral aradation . Thereforadation , IL-1 reradation , and somradation  can easiradation . HoweverIn this study, we kinetically characterized the dynamics of antiviral signaling triggered by RIG-I in human alveolar epithelial (A549) cells and established a mathematical model which allows accurate dynamic simulation. We established an approach permitting the virtually instant stimulation of A549 cells with virus-like dsRNA, leading to a synchronous onset of signaling across all cells and, thus, allowing for a finer resolution of pathway kinetics. With this system, we analyzed phosphorylation and expression of critical proteins in the RIG-I signaling cascade in a fine-grained time course using live-cell imaging, quantitative Western blotting, and qRT–PCR. We used these time-resolved data to establish and calibrate a mathematical model that reproduces the kinetics of key signaling events within the core RIG-I pathway. We combined our RIG-I core model with a previously published and validated model of IFN signaling , ultimatIFNB1 gene  status of RLR signaling pathway components or protein abundance (for IκB) within the IRF3–  or NF–κBnd IFIT1 , and CCL TNFAIP3  were detSupplemental Data 1 for modeling details). Our calibrated model was able to accurately and reliably capture the measured signaling dynamics . To challenge the model with conditions not used for its training, we performed additional experiments in A549 cells with artificially lowered concentrations of IRF3. We used A549 IRF3 KO cells and restored IRF3 to ∼5% of WT level by lentiviral transduction using a weak promoter (murine ROSA26)  representing main steps within the RIG-I signaling pathway based on regular mass-action kinetics. Our model comprises 19 pathway components (“species”) distributed into two distinct compartments (cytoplasm and nucleus), 20 rate constants, and some additional parameters  to account for initial conditions, experimental conditions, and the relative nature of the quantitative immunoblot data . To dete ROSA26) . As expe000-fold . A549 ROWT cells . NotablyWT cells . For furWT cells , compareWT cells , and obsSupplemental Data 1.A mathematical model of the antiviral innate immune response.IFNAR1) and type III (IFNLR) IFNRs, termed IFNR double KO (A549 IFNR DKO), to further characterize RLR signaling dynamics in the presence or absence of IFN feedback (IFIT1 and MX1 (MX1) or 6 h (IFIT1) was unaffected, the lack of IFN feedback in IFNR DKO cells led to a significant decrease in IFIT1 mRNA levels over the following hours and a substantially lower overall induction for MX1 .Having established a dynamic pathway model of the core RIG-I signaling module, we were able to accurately predict the pathway outcome from viral RNA recognition by RIG-I to transcription of IFN-β by IRF3 within the first few hours after RIG-I stimulation . However of 24 h . One comIFNB1, IFIT1, and MX1 over time , whereas others seem to be independent of IRF9 protein levels (IFNB1). The measured outcome of this experimental perturbation of the signaling system was correctly predicted by our model, further corroborating its robustness and reliability . Strikingly, without any further adjustment of kinetic rate constants, the model was capable of adequately describing the mRNA kinetics of IFNB1 and MX1 in HepG2 cells  cell line, HepG2, and compared the ensuing mRNA expression , proteinpression  and IFN pression  were sigpression . Notablykinetics  was idenkinetics . We adapG2 cells . Only exulations . This hiIFNB1, IFNL1, and ISG mRNA and IFN-β secretion upon electro-transfection of dsRNA closely resembling the kinetics observed in A549 and HepG2 cells  and stimulated them by electro-transfection with 5′ppp-dsRNA or infection with vesicular stomatitis virus (VSV). Corroborating the highly similar kinetics of the RIG-I pathway across different cell types, we found rapid induction of G2 cells . NotablyG2 cells . This wapro of CSFV triggers the degradation of IRF3 ; nonetheless, the overall kinetics of induction was not altered significantly. Interestingly, these expression dynamics were also qualitatively predicted by our mathematical model when we systematically reduced MAVS concentrations in silico , mostly by blocking IRF3 . ORF6 negatively impacts IFN induction and IFN signaling Preprinting IRF3 , STAT1, ing IRF3  nuclear ing IRF3 . In A549er assay . By inteer assay , which mer assay . Here, O2 levels .In summary, we established an ODE-based mathematical model of antiviral signaling, comprising the RLR pathway of IFN induction and IFN signaling downstream of the IFNR. This model can very accurately simulate the activation of individual signaling components over time, and the induction of ISGs and the production of antiviral effector proteins. Importantly, it permits in silico simulation of viral interference with this cell-intrinsic defense system and offers a valuable tool to study the impact of yet unknown viral antagonists or other factors perturbing RLR and/or IFN signaling.Preprint). In general, the immune-driven pathogenesis of COVID-19 illustrates the critical importance of timely and well-coordinated cytokine production for a successful immune response, and the potential of a dysregulated IFN and cytokine system to cause substantial pathology . However, in that study, the TLR3 pathway was reported to be co-stimulated and engaged in a novel antagonistic crosstalk with RIG-I signaling. Using CRISPR/Cas9-mediated functional KO of RIG-I or IRF3, we previously controlled for RIG-I-specificity and can rule out significant involvement of TLR3 or other receptors in our system , such as IFIT1 , the fulWe used literature knowledge of the core RIG-I pathway topology to set up a mathematical model based on a set of ODEs mechanistically representing all main canonical signaling steps. We have previously modeled dsRNA recognition by RIG-I and its downstream signaling, however, with a focus on the quantitative output rather than signaling kinetics . Also, BIn contrast to negative feedback regulation of RIG-I, positive feedback (and feedforward) through IFN must be taken into account, in particular, for timeframes of more than 4 h (after which secreted IFN can be detected). Therefore, we coupled our mathematical model to a previously published model of type I IFN signaling . We tookTo further corroborate the cell line independence of the overall rapid signaling dynamics and of our pathway model, we validated it using time-course measurements in the unrelated HepG2 cell line. Again, upon only adjusting the cell line-specific initial protein concentrations, our combined model was able to adequately predict RLR- and IFN-signaling dynamics in HepG2 cells upon electro-transfection of 5′ppp-dsRNA. We further confirmed the overall response dynamics qualitatively in human primary fibroblasts (HFF) upon dsRNA electro-transfection and virus infection, representing a completely unrelated cellular system more closely resembling physiological conditions. In light of the observed high degree of qualitative conservation of pathway dynamics, we expect that our model is generalizable to a wide variety of different cell lines and types by simply adjusting the basal protein concentrations of the proteins involved in signaling. This advertises the model as a valuable tool to study kinetic aspects of antiviral signaling even with experimental measurements only at a limited number of time points. We cannot rule out, however, that in some cell types  further regulatory systems not represented in the model might be in place, or additional transcription factors of  overlapping function may exist that require modifications to the model topology. One such example is IRF7, a transcription factor highly similar to IRF3, which is expressed to high levels in plasmacytoid dendritic cells, rendering them competent to produce excessive amounts of IFN, including IFN-α, even before the positive feedback through the JAK/STAT pathway , 2000.Preprint).As discussed above, negative feedback of the pathway was neglected in the present model as it was not required to accurately describe signaling dynamics in the chosen experimental system. Nonetheless, it is intriguing to contemplate its consequences and relevance. Within virus-infected cells, positive autocrine feedback via IFN signaling increases RIG-I levels, whereas negative feedback via triggered proteolysis or posttranslational modifications counteracts this ; the netpro) both targeting RLR signaling and, thus, inhibiting the induction of IFN, dengue virus NS5 interfering with IFN signaling, and the ORF6 protein of SARS-CoV-2, exhibiting a multi-pronged strategy to inhibit the antiviral system. NS3/4A very efficiently cleaves and inactivates MAVS , but indicates the dominant effect may be at or downstream of IFN production. This was corroborated by modeling, where inhibition of ISGF3 formation approximated the experimental data much closer than limiting IRF3 activity  under the control of the IFIT1 or IFNB1 core promoter was decreased significantly, comparable with HepG2 cells. Hence, we propose ORF6’s potential to interfere with the nuclear translocation of transcription factors, such as IRF3 ; viral RNA at the same time is translated to proteins inhibiting antiviral signaling. We have previously approached modeling the interaction between HCV and innate immune signaling, although at a much lower level of mechanistic detail . Others We present a highly accurate characterization of the dynamics of cell-intrinsic innate immune signaling to virus infection. Using IFN-blind cells, we were able to dissect the induction phase downstream of RLRs and the effector phase downstream of IFNRs, which are normally tightly linked and overlapping. We further used our quantitative time-series data to set up and calibrate the—to the best of our knowledge—most comprehensive mechanistically interpretable dynamic pathway model of the RLR/IFN-signaling network. This model very accurately predicts the kinetics of signaling events downstream of RNA recognition by RIG-I, including the feedback and broadening of the response by secreted IFN and JAK/STAT signaling. Owing to its mechanistic detail, the model is capable of simulating viral immune antagonism and, vice versa, can be used to investigate the mechanism of action of novel virus-encoded inhibitors. Combining models such as ours with models of virus infection and replication will open up new and powerful avenues for studying the dynamics of virus–host interactions.2. Lentiviral transduction was used for the generation of A549 and HepG2 overexpression (OE) cell lines and for A549 KO cell line generation. The CRISPR/Cas9 technology was used for stable KO generation in A549. DNA oligonucleotides coding for guide RNAs (listed in Table S1) against the respective genes were designed with e-crisp.org , supplemented with 10% (vol/vol) or 15% (HFFs) (vol/vol) FCS (Thermo Fisher Scientific), 1x nonessential amino acids (Thermo Fisher Scientific), 100 U/ml penicillin, and 100 ng/ml streptomycin (Life Technologies) at 37°C, 95% humidity, and 5% COrisp.org  and clonrisp.org .Guide RNAs for CRISPR/Cas9 KO generation.Table S1. 4 cells per 24-well. The next day, cells were stimulated with in vitro transcribed and chromatographically purified 400 bp 5′ppp-dsRNA  were used. First, the provided dipping electrode array was used for a mock transfection to decrease the electro-transfection intensity to maximize cell survival and transfection efficiency. Next, DMEM was replaced with 350 μl cytomix and the electrode was inserted into the 24-well plate strictly avoiding the formation of air bubbles. Electro-transfection was performed using the FB-166 program and cytomix was replaced with warm DMEM subsequently. IRF3-GFP nuclear translocation and H2B-mCherry colocalization were analyzed using confocal microscopy equipped with an incubation chamber (Olympus FluoView FV1000) or monitored in short time periods using a 10x magnification in an IncucyteS3 Live-Cell Analysis System (Sartorius AG). Image analysis was conducted with the machine learning software ilastik  and a ShockPod cuvette chamber (Bio-Rad). Cell suspensions containing 4 x 105 HFFs were seeded in the wells of a six-well plate. The following day, the cells were infected on ice by replacing the cell culture supernatant with fresh medium containing , resulting in a MOI of 10. To enhance and synchronize the infection, the plates containing cells were centrifuged at 805g and 4°C for 30 min before transferring to 37°C with 5% CO2. After 1 h, cells were washed with citric acid pH 5 for 5 min to remove any unbound viruses. After a subsequent wash with PBS, the cells were cultured with fresh medium, marking the start of the experiment (time point 0).A total of 5 x 10Synchronously stimulated cells were in-well lysed with 100 μl Laemmli buffer , containing Benzonase Nuclease for 10 min at room temperature, and subsequently incubated at 95°C for 5 min. Protein extracts were separated on 8–12% polyacrylamide gels by SDS–PAGE and transferred to PVDF membranes  in a wet-transfer approach using the Mini Trans-Blot cell (Bio-Rad). Membranes were blocked in PBS-T or TBS-T complemented with 5% (wt/vol) BSA  for up to 3 h at room temperature. Subsequently, the membranes were incubated with PBS-T or TBS-T complemented with 5% BSA and primary antibodies specific for β-actin , calnexin , HA , IFIT1 , IκBα , IRF3 , IRF9 , MAVS , MX1 , NS3 , phospho-IKKα/β , phospho-IKKε , phospho-IRF3 , phospho-NF-κB , phospho-STAT2 , phospho-TBK1 , RIG-I , STAT1  or STAT2  at 4°C overnight. Furthermore, membranes were incubated with anti-rabbit HRP  or anti-mouse HRP  for 1 h at room temperature. For detection, Amersham ECL Prime Western Blotting Detection Reagent (Thermo Fisher Scientific) was applied for 1 min and luminescence was detected using the INTAS ECL ChemoCam Imager 3.2 (INTAS Science Imaging Instruments). Western blot bands were analyzed and quantified using Image J (1.52e).−ΔCt method or fold changes were calculated relative to the 0-h time point using the 2−ΔΔCt method (RNA isolation (New England Biolabs), reverse transcription , and quantitative real-time PCR  were performed according to the manufacturer’s protocols, and qRT–PCR was performed on a CFX96 real-time system (Bio-Rad). Sequences of specific exon-spanning PCR primers are listed in Table S2. Values were normalized to the housekeeping gene GAPDH using the 2t method .Primers for qRT–PCR.Table S2. Quantitative measurement of secreted cytokines within supernatants was performed using the multiplex Meso Scale Diagnostics (MSD) platform. Briefly, supernatants of synchronously stimulated A549 WT, A549 IFNR DKO, and HepG2 WT cells were harvested, centrifuged, and multiplex assays were conducted according to the manufacturer’s instructions. The analytes IFN-β and IFN-λ1 were measured using the human U-PLEX IFN Combo . Plate readout was conducted using the MESO QuickPlex SQ 120 instrument  and measurements were evaluated using the MSD Discovery Workbench software.IFN-β production of VSV-infected HFFs was detected using the LumiKine human IFN-β ELISA kit  according to the manufacturer’s instructions. Lucia luciferase signals were assessed in a Mithras plate reader (Berthold Technologies GmbH & Co. KG).5 cells per well of a 24-well plate were seeded. The next day, the medium was aspirated and replaced with penicillin/streptomycin-free DMEM. 75 ng Firefly luciferase reporter and 25 ng Renilla luciferase reporter were transfected using Lipofectamine 2000 (Invitrogen) following the manufacturer’s protocol. After 8 h, the medium was exchanged and cells were stimulated with SeV (MOI 0.004) for 16 h. Cells were washed with 500 μl PBS, lysed with 100 μl luciferase lysis buffer , and stored for at least 15 min at −80°C. Lysates were thawed and Firefly and Renilla luciferase signals were directly measured in a Mithras plate reader using 400 μl Firefly assay buffer  and Renilla luciferase assay buffer  per well. For multiple well measurements, 100 μl 10% SDS was used to quench the light reaction in between well measurements. Renilla luciferase is constitutively expressed and thus serves as a control. Samples were measured in technical replicates and Firefly luciferase values were divided by Renilla luciferase values.1.5 x 10g, 10 min, 4°C), washed with 80% (vol/vol) acetone, air-dried, and resuspended in 40 μl thiourea buffer . Proteins were pre-digested by the addition of 1 μg LysC in 40 μl 50 mM ammonium bicarbonate buffer (pH 8.0) for 3 h at 25°C. Digestion was completed with 1 μg Trypsin in 120 μl 50 mM ammonium bicarbonate buffer (pH 8.0) for 16 h at 25°C. After purification on C18 StageTips (HepG2 cells) or fractionation of peptides on SCX  and purification on C18 StageTips (A549 cells) as described previously (2O) and buffer B  with a 120-min (A549 cells) gradient  was used at a flow rate of 300 nl/min. In contrast, peptides derived from HepG2 cells were separated with a 180-min gradient. Eluting peptides were directly analyzed on a Q-Exactive HF mass spectrometer (Thermo Fisher Scientific) operated in data-dependent acquisition mode with repeating cycles of one MS1 full scan  at an ion target of 3 × 106, followed by 15 MS2 scans of the highest abundant isolated and higher-energy collisional dissociation fragmented peptide precursors . Peptide precursor isolation for MS2 scans was, in addition, limited by a maximum injection time of 25 ms and an ion target of 1 × 105, whereas repeated isolation of the same precursor was dynamically excluded for 20 s. Spectra were processed with MaxQuant  using label-free quantification, match between runs, fixed carbamidometylation, and variable N-acetylation and methionine oxidation. Peptides and proteins were identified by searching against the human proteome sequences  controlled by a false discovery rate of 0.01 , boiled at 95°C for 8 min and sonicated for 15 min at 4°C (Bioruptor). Alkylation of proteins was performed for 20 min in the dark by the addition of 55 mM iodoacetamide in 50 mM Tris/HCl (pH 7.5), followed by normalization of the protein concentration (Pierce 660 nm Protein Assay). For each replicate, 50 μg proteins were precipitated with 4 vol/vol of prechilled acetone at −20°C overnight, pelleted by centrifugation . 5′ppp-dsRNA was assumed to be uniformly distributed post–electro-transfection, corresponding to a cytoplasmic dsRNA concentration of 2 nM. No basal RIG-I signaling was accounted for, thus, yielding all phosphorylated protein levels to be zero before stimulation. In addition, in the absence of any stimulus, no free IκBα was considered. Total protein levels were converted to concentrations using the reported cytoplasmic and nuclear volume of A549 cells . Background intensities for phosphorylated proteins were defined as mean of normalized intensity values for the first two time points of the short-period experiment . The remaining scaling factors were optimized during the optimization process alongside the kinetic rate constants. Parameter fitting was performed by simultaneously minimizing the negative logarithm of the likelihood for the observed experimental data given our model parameters using a multi-start optimization method based on latin hypercube sampling (LHS) as implemented in the data2dynamics framework for MATLAB , Nine k0⋅μRIG−I . Degrada pathway . The deg pathway . The 11 r MATLAB , 2015. TSupplemental Data 1). IFN and ISG levels were set to zero before stimulation.Whenever possible, parameter values were taken from the previously established RIG-I core model or the original IFN pathway model . AlreadyIFIT1, IFN-λ, RIG-I, MX1), in addition to the already existing up-regulated species IκBα, IFNβ, IRF9, and SOCS. Expression of ISGs is under the regulation of phosphorylated IRF3  or under the regulation of both phosphorylated IRF and active ISGF3 . Depending on the availability of qRT-PCR and Western blot data, ISGs are included at the transcript level , the protein level (RIG-I) or at both levels  as species in our model. Furthermore, we account for a first-order decay of mRNAs (denoted μ) and, when a protein species is included in the model, a translation and protein degradation process.To combine the RIG-I pathway model with the published JAK-STAT model, we included a production rate of IFNpre, that is, the stimulus of JAK-STAT signaling, by the IFN-β mRNA species of our RIG-I pathway core model. The remaining structure of the JAK-STAT model was not changed, but merely additional ISG model species were introduced to better capture the antiviral state of a cell by our model. In total, we considered the expression of six genes in our model  of the Maiwald model   . The degernatant . Model fernatant , 2015. MSupplemental Data 1. The analysis revealed a linear dependency between the shared rate constant for the activation of TBK1/IKKε and the IRF3 phosphorylation rate constant by the two kinases. The shared rate constant for the activation of TBK1/IKKε was consequently fixed and the IRF3 phosphorylation rate was optimized. For all other fitted parameters of the RIG-I core model, no identifiability problems could be identified.Structural and practical identifiability of the core and coupled model were assessed by calculating the profile likelihood estimates for every optimized parameter as implemented in the data2dynamics framework , 2015. BPXD031406.The mass spectrometry data from this publication have been submitted to the PRIDE database and assigned the identifier


Giardia duodenalis is a common pathogenic intestinal protozoan parasite with high prevalence in developing countries, especially among children. The distribution of giardia assemblages among humans and their clinical relevance remains controversial. This study aimed to determine the prevalence and assemblage of Giardia among children under 5 years of age in Jimma, Southwest Ethiopia. Employing a case-control design, 606 children presenting with diarrhea at Jimma university medical center and Serbo Health Center were enrolled from December 2016 to July 2018 along with 617 matched controls without diarrhea. Giardia was detected and typed using real-time PCR. Univariate and multivariate regression analysis was performed. The total prevalence of Giardia was 41% (501/1223) and did not differ significantly between cases and controls (40% vs 42%). Prevalence increased by age, with the highest prevalence seen in children aged ≥ 25 months. Children without diarrhea with a history of diarrhea during the last month were more likely to be Giardia positive compared to children with no history diarrhea . Regardless of current diarrhea symptoms, assemblage B predominated with 89%, followed by assemblage A (8%) and mixed infection assemblage A and B (3%). We report a high prevalence of Giardia by PCR detection in Jimma, Ethiopia, with assemblage B being predominant. There was a similar distribution of Giardia assemblages between children with and without diarrhea. Increasing age was a risk factor for Giardia infection. Community-based prevention and control strategies need to be employed to decrease the risk of giardia infection. Giardia duodenalis  causes Giardia infection in humans and many mammals. It is transmitted through the oral-fecal route following direct or indirect contact with the infectious cyst stages, including human-to-human, zoonotic, waterborne, and foodborne transmission , located 346 km to the southwest of the capital Addis Ababa, and Kersa woreda  located 18 km to the east of Jimma. Jimma town has a total population of 120,960 and is the administrative center for 21 surrounding districts. Jimma is largely coffee producing agrarian community.This study was part of a larger prospective case-control study, which investigated diagnostic accuracy of LED-AP for cryptosporidiosis , or dysentery (at least one loose stool with stains of blood within the previous 24 h). The study included cases with prolonged (7–13 days) and persistent (≥14 days) diarrhea. Community controls without diarrhea in the preceding 48 h were enrolled concurrently by weekly recruitment plans using frequency matching to cases by sex, age stratum, and geographical location of households.Giardia cysts or trophozoites were reported on this result slip. The decision to treat was left with the treating clinical team who followed local standard treatment regimen.Demographic and clinical data were collected by study nurses using standardized case report forms by interview and from hospital records. All parents/caretakers of the participants were instructed and asked to provide a stool sample of their children with a screw-cap plastic container. Aliquots of stool samples were stored at −80°C until shipment to Vestfold Hospital Trust, Norway, for further processing. During the time the study was conducted a wet microscopy was performed as soon as the stool sample reached the laboratory. A result slip with the wet microscopy findings was immediately brought back to the treating health care worker (doctor or nurse). The presence or absence of Giardia was detected using real-time qPCR run on a Light Cycler 480II, Roche, including primers and probes for the internal control   500 μl S.T.A.R. buffer (Roche) + 500 μl BLB  and vortexed, and the stool-buffer suspension was kept frozen. Stool-buffer suspension was then used for nucleic acid extraction with MagNA Pure 96 instrument, MagNA Pure 96 DNA, and Viral NA Large Volume Kit, and eluted in 100 μl. G. duodenalis positive samples were further analyzed using an assemblage-specific real-time PCR assay  values and melting curve values were recorded.All Giardia. Results were interpreted using odds ratios, 95% confidence intervals, and significance levels. For analysis of acute malnutrition, children < 6 months, severe acute malnutrition (SAM) was defined as weight for-height z-score (WHZ) ≤ −3 of the WHO standard curves  were males and 549 (45%) were females. Out of 1223 children, 58% and 42% were from Serbo and Jimma study sites respectively. The most common age category was 7–12 months (33%), followed by the 13–24 months (32%). Using anthropometric measurements most children (88%) had no acute malnutrition, 51% kept animals in the house and 98% of children with diarrhea had acute diarrhea lasting less than 14 days  in cases and 42% (261/617) in controls. The prevalence of Giardia in participants of this study was not significantly different among cases and controls OR 1.1, 95% CI (0.9–1.2). Because history of diarrhea in the last one month was a risk for detecting G. duodenalis in stool, we did sensitivity analysis by excluding children with history of diarrhea in the past month. The prevalence of Giardia was quite similar in cases and controls 41%, 212/522 vs. 38%, 193/506 OR 1.12, 95% CI (0.9–1.4). We further assessed the quantity of G. duodenalis in the samples based on the Cq values obtained in qPCR using non-parametric test. We found a higher quantity of Giardia among children without diarrhea  compared to children with diarrhea  (P=0.006).Of the 1223 study participants, 606 and 617 were cases and controls, respectively. The prevalence of G. duodenalis and different demographic and clinical characteristics in univariate and multivariate analysis, respectively. The prevalence of G. duodenalis in study participants was increasing with age, the highest prevalence was seen among children ≥ 25 months in both cases and controls, OR 23.75, 95% CI (10.31–54.73) P = <0.001. Children without diarrhea, with a history of diarrhea in the past month had increased risk of having a Giardia positive stool sample . Other demographic or clinical characteristics such as sex, nutritional status, domestic animals in the house, type of diarrhea, and vomiting were not associated with Giardia infection.Tables G. duodenalis PCR positive samples, 281 (56%) samples could be typed of which 132 and 149 samples were from children with diarrhea and children without diarrhea respectively. Assemblage B was found in 89% of samples followed by assemblage A (8%) and 3% was a mixed infection of assemblage A+B. Chi-square test was used to compare the differences in proportion of Giardia assemblage types in cases and control; results in Table P=0.48) of the assemblage types between cases and control samples. We further assessed distribution of assemblages in two different age groups i.e., children aged <24 months (n=165) and children above 24 months (n=116). Out of 165 samples from children aged <24 months, 147 (89%) had assemblage B, while 15 (9%) and 3 (2%) had assemblage A and mixed assemblage A+B respectively. From 116 samples of children aged >24 months, 104 samples (90%) had assemblage B, 7 (6%) had assemblage A, and 5 (4%) had mixed assemblage A+B. There were no significant age differences in G. duodenalis assemblage distributions.Out of a total of 501 Giardia infection among pediatric population in Jimma Ethiopia. Additionally, to the best of our knowledge, this is one of the first studies to use assemblage-specific PCR and employing a case-control design in children under 5 years in Ethiopia.This study is one of the few studies assessing the prevalence, assemblage, and risk factors of G. duodenalis among participants in this case-control study was 40%. In earlier studies within the country, some indicated a lower prevalence of 10–18% (Birrie and Erko G. duodenalis prevalence; Kenya 4.5% (Mbae et al. Giardia prevalence of 60.1% and 87%, respectively. The marked variation in G. duodenalis prevalence is likely related to the varying sensitivity of the diagnostic methods used across studies. Studies which used PCR, generally considered a more sensitive method (Stensvold and Nielsen G. duodenalis detection increased with age. Studies which included older children like Rwanda (Ignatius et al. G. duodenalis prevalence. Thirdly, geographical variation and socio-economic factors, such as access to safe drinking water, sanitation, and hygiene practices, may also be the cause of variation in G. duodenalis prevalence (Nundy et al. G. duodenalis of 4.6% and 16.8% despite using PCR.Based on diagnostic real-time PCR, the overall prevalence of G. duodenalis among participants in this case-control study without significant differences even after removing from the analysis children with a history of diarrhea in the past month. Children without diarrhea with G. duodenalis may serve as parasite reservoirs. Several studies in developing countries reported higher prevalence of G. duodenalis in controls than in cases with acute diarrhea (Tellevik et al. Giardia in both case and control groups serves as a compelling indication that waterborne pathogens are commonly transmitted among the studied age groups. Consequently, future research endeavors should explore detection of additional pathogens such as bacterial and viruses to precisely identify the specific etiological factors contributing to diarrhea within this study cohort.We found high prevalence of G. duodenalis infection was significantly associated with increasing age. Age-related increase in prevalence of infection has also been observed in other studies (Mbae et al. Giardia detection from stool. This could be due to prolonged shedding of G. duodenalis cyst in stool from the previous diarrhea episode or asymptomatic giardiasis. No other demographic or clinical characteristic assessed in our study such as sex, acute malnutrition, and keeping animals in the house were associated with G. duodenalis.G. duodenalis assemblage B was the predominant subtype with a prevalence of 89%. Similarly, assemblage B was reported in higher frequency than assemblage A in previous studies conducted in Ethiopia (de Lucio et al. G. duodenalis assemblage may partly be explained by either the genetic diversity of G. duodenalis circulating in different geographical areas or the difference in the dynamics of transmission. There are controversial reports on the role of G. duodenalis assemblages and clinical symptoms (Haque et al. G. duodenalis assemblages between children with and without diarrhea. However, studies from Rwanda, Australia, and Bangladesh have shown that G. duodenalis assemblage A was more likely to be found in symptomatic diarrheic children (Ignatius et al. G. duodenalis assemblage B (Molina et al. G. duodenalis assemblage and diarrhea symptoms. In the present study mixed infection of G. duodenalis assemblage A and B was found in 3 percent of cases and has been reported previously in Ethiopia and other countries (Hijjawi et al. G. duodenalis suggests the intricate circulation of the parasite within the environment and study participants may have been exposed to multiple sources of infection (Tamura et al. G. duodenalis assemblages and other clinical or socio-demographic parameters. This could be due to the strong dominance of assemblage B in our sample set which resulted in low power to assess correlations.One of the limitations of the present study was that only 50% of the samples could be typed. Based on the assemblage-specific real-time PCR employed, G. duodenalis in rural areas, has also been reported in other studies (Samie et al. G. duodenalis infection prevalence during the rainy season was observed in studies conducted in Zambia (Siwila et al. Higher risk of G. duodenalis in this study from Jimma Ethiopia. Assemblage B was the predominant type causing giardiasis in this region. Giardia prevalence increased with age. The occurrence of diarrhea symptoms was not associated with G. duodenalis infection, nor with Giardia assemblage.Using PCR method, we report a prevalence of 41% of