Trypanozoon subgenus has a unique sequence. As previously shown in blood from Guinean human African trypanosomiasis (HAT) patients, SL-RNA is an accurate target for diagnosis. Detection of SL-RNA in the cerebrospinal fluid (CSF) has never been attempted. In a large group of Congolese gambiense HAT patients, the present study aims i) to confirm the sensitivity of SL-RNA detection in the blood and; ii) to assess the diagnostic performance of SL-RNA compared to trypanosome detection in CSF.Spliced Leader (SL) trypanosome RNA is detectable only in the presence of live trypanosomes, is abundant and the p = 0.001). Of 96 CSF RNA specimens, 65 (67.7%) were SL-RNA positive, but there was no significant difference between sensitivity of SL-RNA and trypanosome detection in CSF. The contribution of DNA to the Cq values was negligible. In CSF with normal cell counts, a fraction of SL-RNA might have been lost during extraction as indicated by higher internal extraction control Cq values.Blood and CSF from 97 confirmed gambiense HAT patients from the Democratic Republic of Congo were collected using PAXgene blood RNA Tubes. Before RNA extraction, specimens were supplemented with internal extraction control RNA to monitor the extraction, which was performed with a PAXgene Blood RNA Kit. SL-RNA qPCR was carried out with and without reverse transcriptase to monitor DNA contamination. In blood, 92/97 (94.8%) HAT patients tested SL-RNA positive, which was significantly more than combined trypanosome detection in lymph and blood .This study was an integral part of the diagnostic trial "New Diagnostic Tools for Elimination of Sleeping Sickness and Clinical Trials: Early tests of Cure" (DiTECT-HAT-WP4, ClinicalTrials.gov Identifier:  Human African trypanosomiasis is a parasitic infection occurring in sub-Saharan Africa, which is fatal if left untreated. Diagnosis relies on demonstration of trypanosomes, which may occur at such low concentrations that they remain microscopically undetectable. Nucleic acid detection offers an alternative, in particular RNA, which is unstable and a better marker for live organisms than DNA. Trypanosomal SL-RNA detection in blood by reverse transcriptase quantitative PCR has hitherto only been tested twice. Although in cerebrospinal fluid, trypanosome presence indicates brain infection, SL-RNA detection has never been attempted. We evaluated sensitivity of SL-RNA detection in blood and cerebrospinal fluid. For each specimen, 2 controls were included: presence of genomic DNA contamination and efficacy of RNA extraction. Sensitivity of SL-RNA detection in blood was higher than of combined blood and lymph microscopy. In cerebrospinal fluid, SL-RNA and trypanosome detection had similar sensitivity. In a few specimens, traces of DNA were amplified. In some cerebrospinal fluids, some RNA was lost during extraction. Performing both internal controls is crucial, to ensure that negative SL-RNA cerebrospinal fluid findings are not due to a failed extraction and, in particular when testing treated patients, to differentiate live parasite RNA from reminiscent DNA. Trypanosoma brucei (T.b.) gambiense in Central and West Africa and by T.b. rhodesiense in East Africa. In humans, presence of the trypanosome in the blood and lymph only, corresponds to the first stage of the disease, whereas the second stage is characterized by trypanosome invasion of the central nervous system.Human African trypanosomiasis (HAT) or sleeping sickness is a neglected tropical disease caused by T.b. gambiense HAT, by the low and fluctuating trypanosomal load in these body fluids, intrinsic to the parasite and its interaction with the host’s immune response. The resulting low sensitivity of microscopic diagnosis, implies a risk of failure to detect the parasite although a patient is actually infected [The diagnosis of HAT is primarily based on the detection of the parasite in the blood, lymph or cerebrospinal fluid (CSF) . Performinfected .PCR targeting parasite DNA presents an alternative for the diagnosis of HAT . HoweverTrypanozoon subgenus has a unique sequence. SL-RNA is involved in the maturation of messenger RNA to which it is attached [T.b. gambiense, the specificity of SL-RNA detection in blood was higher than that of DNA detection by PCR [The detection of trypanosomal RNA, which is unstable and produced only by live parasites, demonstrates an active infection in the host and thus enables to establish a definite diagnosis. Spliced Leader (SL) trypanosome RNA can be used for diagnostic purposes, as it is abundant in trypanosomes and the attached . The diaattached ,6. Also n by PCR . To datend stage HAT, stage determination loses importance as new stage-independent treatments for sleeping sickness emerge [Although presence of trypanosomes in CSF has traditionally been a marker for 2s emerge –9. Nevers emerge . Also fos emerge ,12. The This study was an integral part of the diagnostic trial "New Diagnostic Tools for Elimination of Sleeping Sickness and Clinical Trials: Early tests of Cure" . The DiTECT-HAT-WP4 study has received approval from the “Comité Consultatif de Déontologie et d’Ethique” (CCDE) of the French National Institute for Sustainable Development Research , from the institutional Review Board of the Institute of Tropical Medicine (reference 1096/16), and from the Ethics Committees of the Ministry of Health, DRC through the Ngaliema Clinic of Kinshasa (September 2016 session) and the School of Public Health of the University of Kinshasa (reference ESP/CE/136/2020). It was carried out in conjunction with a prospective therapeutic trial conducted by DNDi  on the new drug Acoziborole for HAT that was approved by the CERSAC, Ethics Committees of the Ministry of Health, DRC through the Ngaliema Clinic of Kinshasa and the CNES , DRC.Participants first gave their informed consent to participate in the therapeutic trial. A separate written informed consent was obtained next before their inclusion in the DiTECT-HAT-WP4 study. For minors participating in the DiTECT-HAT-WP4 study, an additional written consent was obtained from their legal representative.The DiTECT-HAT-WP4 study was conducted in Democratic Republic of the Congo from February 2017 until March 2019. Patients were recruited in five reference district hospitals that were conducting the DNDi-OXA-02-HAT therapeutic trial under the supervision of the PNLTHA, located in Dipumba and Katanda in the province of Kasaï Oriental, Ngandajika in the province of Lomami, Masi Manimba in the province of Kwilu and in Kinshasa.T.b. gambiense parasites in blood, lymph and/or CSF; age ≥15 years; give and sign the study consent form; Karnofsky index > 50; able to take tablets orally; have a permanent address or being retrievable by other people; able to comply to the follow-up visits schedule and to other constraints of the study and accept to be hospitalized for acoziborole treatment and study procedures. As all HAT patients participating in DiTECT-HAT-WP4 were first enrolled in the DNDi-OXA-02 study, they were treated with acoziborole, independent of their disease stage.Patients included in the DITECT-HAT-WP4 study were enrolled first in the DNDi-OXA-02-HAT study. The inclusion criteria for DiTECT-HAT-WP4 corresponded to those applied in the DNDi-OXA-02-HAT study: confirmed HAT with T.b. gambiense test or a rapid diagnostic test for gambiense HAT). Individuals who were positive in a serological test underwent parasitological examination. For persons with swollen cervical lymph nodes, a lymph aspirate was examined for trypanosomes by microscopy. For persons positive in a serological test but negative in lymph or without swollen lymph nodes, blood was examined for trypanosome presence by mini anion-exchange centrifugation technique on buffy coat (mAECT-BC)[Patients included in this study were diagnosed either in the village by mobile teams (active screening), or at the reference district hospital (passive screening). Screening consisted of identifying characteristic clinical signs, in particular swollen cervical lymph nodes, and serological tests (CATT/mAECT-BC). If mAECmAECT-BC). The patwww.PreAnalytiX.com) according to the instructions of the manufacturer. After the collection of CSF for direct examination, the PAXgene Blood Tube was opened and 2.5 ml of CSF were collected by holding the tube under the lumbar puncture needle, after which the tube was closed. Both blood and CSF samples collected in PAXgene Blood RNA Tubes were inverted at least 10 times, and decanted immediately into 10 ml cryotubes. They were stored at -20°C for maximum 2 months before transport in liquid nitrogen to the HAT National Reference Laboratory at the Institut National de Recherche Biomédicale (INRB) in Kinshasa, where they were stored at -80°C until RNA extraction.From each HAT patient, 2.5 ml of blood were collected in a PAXgene Blood RNA Tube . The samples were thawed by placing them at ambient temperature for 4 hours to ensure full lysis before centrifugation and start of the extraction process. The pellet was lyzed and supplemented after centrifugation with 4 μl RNA internal extraction control (IEC) according to manufacturer’s recommendations . Briefly, the resuspended pellet was proteinase K treated, and residual cell debris removed through PAXgene shredder spin column centrifugation. Ethanol was added to the flow-through fraction and the lysate applied to a PAXgene RNA spin column centrifugation. The bound RNA was treated with DNase I and after several wash steps, RNA was eluted in 80 μl and stored at -80°C. RNA extracted from human blood spiked with T.b. gambiense LiTat 1.3 served as positive control.RNA extraction on blood and CSF samples collected in PAXgene Blood RNA Tubes was performed using a PAXgene Blood RNA Kit IVD following the guidelines of the manufacturer  with 400 nM of primers 5′-CAATATAGTACAGAAACTG-3′ (cSL) and 5′-AACTAACGCTATTATTAGAA-3′ (SL-F) (IDT Integrated DNA Technologies) and 4 μl RNA eluate in a final volume of 20 μl. All RNA extracts were tested in duplicate, and with (RT) or without (noRT) addition of reverse transcriptase (RT) . Cycling conditions using AriaMX Real-Time PCR System Machine  were 45°C for 10 minutes, 95°C for 2 minutes, and 40 cycles of 95°C for 2 seconds, 50°C for 10 seconds and 60°C for 5 seconds. The melting curve was recorded between 45°C and 95°C, using increments of 0.5°C for 5 seconds. Each qPCR run included a positive control from the spiked An RNA extract was considered positive for SL-RNA if both RT replicates were associated with a melting temperature (Tm) between 65 and 68°C. When detected, the Cq of the noRT reaction was used to calculate the percentage contribution of genomic DNA to the Cq-value of the RT reaction according to the following equation :%gDNA= and 5 μl of RNA extract in a 20 μl reaction. Cycling conditions using AriaMX Real-Time PCR System Machine  were 50°C for 10 minutes, 95°C for 2 minutes and 40 cycles of 95°C for 2 seconds, 50°C for 10 seconds and 60°C for 5 seconds.p value.For proportions, binomial confidence intervals with a 95% confidence level (CI) were calculated. The categorical results of trypanosome and SL-RNA detection in the same patients were compared by the Mc Nemar Chi square test. The Cq values of the IEC of two groups of patients were compared by an unpaired t-test, determining the two-tailed In total, 97 parasitologically confirmed HAT patients were included in DiTECT-HAT-WP4, 53 in Masi Manimba, 23 in Dipumba, 9 in Katanda, 10 in Ngandajika and 2 in Kinshasa. The median age of the participants was 31 years (interquartile range 24–44). The sex ratio was 50 females for 47 males. The CATT test was positive in 100% of patients on whom it was performed (95/95), the remaining two patients, on whom CATT was not performed, were positive in SD Bioline HAT. The parasitological results of these HAT patients are summarized in Swollen lymph nodes could be punctured in 53 patients, and lymph was trypanosome positive for 35/53 HAT patients included in the study . Next, blood was examined for 68 patients, and trypanosomes were detected in blood for 45 of 68 included HAT patients . Lymph or blood were trypanosome positive in 78/97 HAT patients . In total 69/97  HAT patients had trypanosomes in CSF, including all 19 patients in whom trypanosome infection could not be demonstrated previously in lymph and blood.Fourteen HAT patients were classified in early stage , 7/97 in intermediate stage  and 76/97 in late stage . All of them were SL-RNA positive, either in CSF and/or blood. Detailed results are shown in The internal extraction control added to each blood specimen during the RNA extraction procedure was detected by RT-qPCR in all 97 extracted blood specimens with a mean Cq value of 20.9 (standard deviation 1.0).Of 97 confirmed HAT patients, 92  tested SL-RNA positive in blood . The conp = 0.0001, 63 SL-RNA versus 45 parasite positives). SL-RNA detection in blood was also significantly more positive than combined lymph and blood parasite detection .Four out of 5 SL-RNA negative specimens  did not show amplification  and/or had a RT Cq value <40 but a melting temperature far outside the 65–68°C range. One negative specimen (patient 49) showed one positive reaction (Cq 33.6 and melting temperature 66°C) and one negative reaction . In only one of these blood SL-RNA negative patients, trypanosomes had been detected in blood and CSF (patient 58), while in the other 4 , trypanosomes had been detected in CSF only. Video recordings reconfirmed microscopic parasite finding for these 5 SL-RNA negatives. In the 68 patients in whom trypanosome presence in blood had been examined, SL-RNA was significantly more positive than trypanosome detection  and 7  were SL-RNA positive. Of 76 patients in late stage, 71  had SL-RNA positive results .Of 97 patients included, 96 CSF RNA specimens were available (CSF RNA specimen of patient 93 missing). The internal RNA extraction control added to each CSF specimen during the RNA extraction procedure was detected by RT-qPCR in all 96 specimens with a mean Cq corresponding to 25.4  were SL-RNA positive . Again, p = 0.5, 65 SL-RNA versus 68 modified single centrifugation positives).Of 14 early stage patients, zero  had SL-RNA in CSF, while of 7 patients in intermediate stage, one  reacted SL-RNA positive (patient 20). Of 75 CSF specimens from late stage patients, 64  contained SL-RNA. From 7 patients in late stage without trypanosomes in CSF, 2  were CSF SL-RNA positive (patients 22 and 27). From 68 late stage CSF samples containing trypanosomes, 62  were SL-RNA positive. In 6 patients who were SL-RNA negative but reported as modified single centrifugation positive , retrospective analysis of the video recordings reconfirmed presence of live trypanosomes in the CSF. There was no significant difference in the number of SL-RNA or trypanosome positives  are processed. A second control step introduced in the protocol was parallel qPCR analysis of the specimen without addition of reverse transcriptase. This enables the calculation of the contribution of genomic DNA to the obtained RNA result, thus guaranteeing that RNA was effectively detected instead of remnant DNA. Moreover, as it has been estimated that half-live of most trypanosomal mRNA is less than 100 minutes , the dettage HAT , which itage HAT . In the The present study also has some limitations. First, although we were able to demonstrate the high sensitivity of RNA detection in blood of HAT patients, we could not determine the specificity of the test, as no specimens from non-HAT control individuals had been collected. However, in 2 previous studies using a similar protocol in Guinea, specificities of respectively 96 and 100% were observed in 49 and 32 endemic healthy controls ,6. The sIn this study, the sensitivity of SL-RNA detection in the blood for diagnosis of HAT was 95.8% (CI 89.8–98.8%). In the past, the value of this parameter was determined at 92% (CI 78–97%)  and alsoDetection of trypanosomes in CSF is a marker for the diagnosis of second stage HAT . Howevera posteriori confirmation of HAT in serological suspects who undergo treatment without parasitological examination, as could be the case in future “test and treat” algorithms [The high sensitivity of SL-RNA RT-qPCR opens the door for future diagnostic applications. However, as for PCR in the past, SL-RNA is, for the moment, not really suitable for routine diagnosis of HAT under field conditions in rural areas where HAT occurs. It requires demanding and critical logistics, including correct specimen collection on RNA stabilization buffer, and transport of the stabilized RNA soon after collection or frozen from the HAT treatment center to a reference lab for proper RNA extraction, which cannot be expected in routine . In addigorithms .T.b. gambiense should be explored further. In particular the high sensitivity of RNA detection in blood could open the door for less invasive diagnosis of relapses, avoiding lumbar puncture. Furthermore, as recently new RNA detection tests have emerged which have only been tested experimentally, including 7SL-derived small RNA [Future research should confirm specificity of RNA detection and confirm its sensitivity in CSF. The performance of detection of SL-RNA as a marker for the diagnosis of relapses during post-treatment follow-up of patients with mall RNA , future In conclusion, with the present study, we confirmed the elevated sensitivity of SL-RNA detection in the blood of HAT patients and demonstrated the diagnostic performance of SL-RNA detection in CSF for the first time, which is a first step towards new applications of RNA detection.


Caenorhabditis elegans Prop1-like homeobox gene unc-42 is expressed in 15 distinct sensory, inter- and motor neuron classes throughout the entire C. elegans nervous system. Strikingly, all 15 neuron classes expressing unc-42 are synaptically interconnected, prompting us to investigate whether unc-42 controls the functional properties of this circuit and perhaps also the assembly of these neurons into functional circuitry. We found that unc-42 defines the routes of communication between these interconnected neurons by controlling the expression of neurotransmitter pathway genes, neurotransmitter receptors, neuropeptides, and neuropeptide receptors. Anatomical analysis of unc-42 mutant animals reveals defects in axon pathfinding and synaptic connectivity, paralleled by expression defects of molecules involved in axon pathfinding, cell-cell recognition, and synaptic connectivity. We conclude that unc-42 establishes functional circuitry by acting as a terminal selector of functionally connected neuron types. We identify a number of additional transcription factors that are also expressed in synaptically connected neurons and propose that terminal selectors may also function as ‘circuit organizer transcription factors’ to control the assembly of functional circuitry throughout the nervous system. We hypothesize that such organizational properties of transcription factors may be reflective of not only ontogenetic, but perhaps also phylogenetic trajectories of neuronal circuit establishment.Many neuronal identity regulators are expressed in distinct populations of cells in the nervous system, but their function is often analyzed only in specific isolated cellular contexts, thereby potentially leaving overarching themes in gene function undiscovered. We show here that the  Individual gene regulatory factors are usually expressed in multiple cell types of a developing nervous system, yet their function is often only studied in specific cellular contexts. Many examples illustrate this regional bias in understanding gene function. For instance, the function of the mouse Brn3a POU homeobox gene has been extensively studied in some parts of the central nervous system, such as retinal ganglion cells, habenula, or peripheral sensory organs, but Brn3a function remains largely unexplored in other regions where the gene is expressed, including the interpeduncular nucleus or the superior colliculus (reviewed in Caenorhabditis elegans nervous system (118 neuron classes), genetic loss-of-function analysis of specific regulatory factors has also often focused on individual genes in specific cellular contexts. This bias often originated from the phenotype by which a gene was retrieved through mutant screens. For example, the unc-30/Pitx transcription factor, one of the first neuronal differentiation genes cloned in C. elegans  neuron classes into functional circuitry, with ensuing deleterious consequences for proper locomotory behavior. Prompted by our analysis of unc-42, we examined whether other transcription factors also show a biased expression in synaptically connected neurons. We found many examples of such associations suggesting the existence of ‘circuit organizer transcription factors’ that operate in overlapping sets of interconnected neurons to instruct the assembly of a nervous system. We discuss the evolutionary implications of our findings.We describe here our nervous system-wide analysis of the comotion , and thecomotion . Vertebrcomotion , but thecomotion . Previourneurons . Moreoverneurons . More re neurons , the AIB neurons , the AVK neurons , and the neurons . Howeverunc-42 transcription factor was previously analyzed using antibody staining and reporter constructs including 2.6 kb of sequences upstream of the unc-42 locus  cells at the 1.5-fold stage  neurons include sensory, inter-, and motor neurons and display distinct neurotransmitter identities  . Moreoveunc-42-expressing neurons are synaptically connected. We found that unc-42-expressing neurons indeed are more likely to be synaptically connected to each other than neuron pairs sampled at random from the whole connectome   analysis, with an appropriate null model that takes into account membrane contact  to estimanalysis  that is analysis . Since manalysis . This ansis (−5) .We further extended these two synaptic association tests to all members of the homeobox gene family that are selectively expressed in a subset of neurons in the mature nervous system . This anunc-42(+) neurons includes a single sensory neuron involved in nociceptive behavior  neurons  neurons to exert their proper function.The set of behavior  and downbehavior . Using abehavior , we foun neurons . This ma mutants . Togetheory cues , this anunc-42 expression to a set of synaptically highly interconnected neurons made us first ask whether unc-42 affects neuronal communication among the unc-42(+) neurons, using again the canonical e419 nonsense allele. To this end, we systematically examined the expression of enzymes and transporters that mark the distinct neurotransmitter identities of the unc-42(+) neurons. Some of this analysis had already previously been done for 6 of the 15 unc-42(+) neurons: unc-42 was shown to be required for the glutamatergic identity of the ASH and AIB neurons, as assessed by loss of eat-4/VGLUT expression (unc-17/VAChT and cho-1/ChT expression (unc-42(+) circuit. We found that loss of unc-42 affects unc-17/VAChT expression and hence cholinergic identity in all but one of the normally unc-42(+) neurons  neurons  receptors, acr-2 and acr-15, in the unc-42(+) circuit. The expression and unc-42 dependence of the ionotropic Glu receptors had been examined before (unc-42(+) cells than previously reported likely explained by our usage of updated reagents that more precisely identify neuron classes. We found the expression of each of these genes to be affected in a cell type-specific manner in unc-42 mutants  receptors, d before . However mutants .unc-42 also affects the expression of cholinergic receptor systems, specifically the AChR subunits acr-2 and acr-15 in the RIV, RMD, SAA, and SMD neurons and expression of the AChR-like des-2 gene in the AVD neurons (unc-42(+) circuit responsive to tyramine signaling from the RIM neurons  neurons (unc-42 on neurotransmitter expression (presynaptic neurotransmitter synthesis/transport and/or postsynaptic neurotransmitter) is often not fully expressive or fully penetrant, indicating that unc-42 is not the sole determinant of these neuronal identity features. This is a recurrent theme in the analysis of unc-42 function throughout this paper. We will return to this point at the end of this paper when we discuss transcriptional cofactors of unc-42.Moving from glutamatergic receptors to cholinergic receptors, we found that loss of  neurons . Moreove neurons , is affe mutants . A summa neurons . We noteunc-42(+) neurons. Previous work has already shown three neuropeptides  and one neuropeptide receptor (npr-9) to be dependent on unc-42 in specific neuron types  and the flp-18 neuropeptide binds to the npr-4 and npr-11 receptors (unc-42(e419) mutant animals   , therebybed here . Among t neurons . npr-11  animals , animals mutants .unc-42 function, we analyzed the behavior of animals that lack the neuropeptide flp-21 and the neuropeptide receptors ntr-1 and ntr-2. We found that, like unc-42 mutants, flp-21 and ntr-2 mutant animals displayed decreased backward motion (flp-21 is regulated by unc-42 in the ASH neuron (unc-42 were head bend mean (ntr-1 and ntr-2) and absolute midbody speed (ntr-1)  . The neuunc-42 may also affect signaling via other internal signaling systems. We infer this from the observation that unc-42 also affects the expression of the orphan GPCR sra-11 in the AVB neurons  circuit is provided by the polymodal ASH neurons. Among other modalities, ASH senses high osmolarity  nociceptive reflex circuit.Direct sensory input into the molarity  and this mutants . A putatd in ASH , and osm mutants . ASH als mutants . The exp  into functional circuitry. We first examined systematically and quantitatively whether neurons that normally express UNC-42 are generated and whether their soma adopt their correct positions in unc-42 mutant animals. To this end, we again used the NeuroPAL neuronal landmark strain, which labels the position of all neurons with a number of markers, including a panneuronally expressed marker  neurons. This proved to be a substantial challenge because, as we described above (and further below), the vast majority of molecular markers that label individual unc-42(+) neurons fail to be expressed in unc-42 mutant animals. Two exceptions include the srd-10::gfp transgene that labels ASH axodendritic morphology and the hlh-34::gfp transgene that labels the morphology of the AVH interneuron. Since the expression of both reporters is either not affected or only mildly affected in unc-42 mutants, they allowed us to visualize ASH and AVH process outgrowth, revealing that unc-42 is indeed required for proper axon extension of both neuron classes; unc-42 is required for proper AVH axon extension along the ventral nerve cord, and unc-42 is required for ASH axons to reach the dorsal midline   . This ap mutants . The app neurons , none of  allele was used, which contains a missense mutation in a highly conserved residue of the homeodomain (unc-42(+) neurons are made. Tracing processes through 309 sections, we were able to assign a total of 19 processes to specific neuron types, 8 of which normally express unc-42 .The effect of croscopy . For thieodomain . We sectunc-42 does not affect the overall relative arrangement of the 19 identified neuronal processes with the part of the nerve ring that we were able to analyze (unc-42 mutants (unc-42 (unc-42 in the pre- and postsynaptic neurons (unc-42(+) is between the interneurons SAAVL and AVAL. For this connection, the wild type animal makes 22 synapses across 50 serial sections and the unc-42 mutant animal makes only 2 synapses across two serial sections in spite of the normal adjacency of the two processes. In addition to connections where both the pre- and postsynaptic neurons are normally unc-42(+), some of the connections where only the postsynaptic neuron is normally unc-42(+) are also disrupted. For example, in the connection between the presynaptic unc-42(-) sensory neuron OLLR and the postsynaptic unc-42(+) motor neuron SMDVL, the wild type animal makes five synapses in a total of 11 sections, whereas the unc-42 mutant animal makes only one synapse across two sections. The above-mentioned process adjacency data indicates that the synaptic defects that we observed cannot be explained by loss of adjacency alone. For example, the wild type SAAVL and AVAL processes are adjacent for 158 sections, whereas in the unc-42 mutant animal these two neurons are adjacent for 131 sections, a reduction much milder than the loss of chemical synaptic connectivity . In conclusion, our fine-grained anatomical analysis reveals that while axons are placed correctly in the analyzed unc-42 mutant animal, there are defects in the generation of synaptic contact. This is consistent with the hypothesis that unc-42 is required for proper circuit assembly.We found that loss of  analyze . We quan mutants . In term  neurons (unc-42(+) nociceptive circuit. inx-18a and inx-19 show a particularly good match, and we examined the expression pattern in unc-42 mutant animals. We found that in unc-42 mutant animals inx-18a and inx-19 expression is selectively downregulated in those neurons that normally express unc-42. Specifically, inx-19 expression is affected in ASH sensory neuron, AVA, AVB, AVD, and AVE command interneurons, in the peptidergic AVK interneurons, and the RMD head motor neurons  null mutants (n = 91), comparable to what is observed in unc-42 mutants (unc-42 mutants unc-6/Netrin expression (as assessed with an unc-6 fosmid-based reporter reagent)   is elimireagent) . We attepression . No earlunc-42(+) neurons also express a host of cell surface molecules with potential roles in axon pathfinding and synapse formation. We examined 10 cell surface proteins (nine of them of the IgSF family members) that show expression in subsets of unc-42(+) neurons for their dependence on unc-42. These include genes previously shown to be involved in axon pathfinding and/or axon fasciculation  and/or organizing synaptic structure and/or function  (rig-1 and rig-5). These proteins display a unique combinatorial expression in each unc-42(+) neurons (with the exception of AVK and AVH). We found that expression of each one of these 10 genes is profoundly affected in unc-42 mutant animals  , as well animals , summariunc-42-dependent nociceptive reflex circuit, we tested animals that carry mutations in either of seven of the unc-42-dependent cell recognition molecules for locomotory defects. We found that nlg-1/Neuroligin and three IgSF members, rig-6/Contactin, ncam-1/NCAM and rig-3 phenocopy subsets of the unc-42 locomotory defects . ncam-1(-) animals also phenocopy unc-42(-) animals in regard to increased pausing, a behavior that is controlled by the AIB neuron, where the expression of ncam-1 is unc-42 dependent. nlg-1 mutants phenocopy unc-42 mutants in decreased backwards motion, a behavior that is controlled by the AVA command interneuron, where the expression of nlg-1 is unc-42-dependent . Nevertheless, the phenocopy is an encouraging prerequisite for being a functionally relevant target of unc-42.To assess possible function of these cell surface molecules in the  defects . Similarependent . Cases irab-3::gfp marker) of a subset of unc-42(+) neurons  in rig-6, rig-3, ncam-1, and nlg-1 mutants (unc-42(+) neurons.We observed no obvious defects in axon pathfinding or synaptic vesicle clustering  neurons.The analysis described above raises a number of questions. First, does UNC-42 control the many target genes described above directly or indirectly? Second, how does UNC-42 activate distinct target genes in distinct neuron types? Using the single cell transcriptome atlas of all  neurons  and a phunc-3 affects the cholinergic identity of command interneurons in a manner similar to the unc-42 effect  neurons? The most parsimonious explanation is that UNC-42 requires neuron-type-specific cofactors to activate distinct sets of neuron class-specific gene batteries. We found this scenario to indeed apply in many UNC-42(+) neuron classes. For example, we had previously shown that the EBF/Collier ortholog 2 effect . Consist2 effect . To funcrneurons .cfi-1 transcription factor causes differentiation defects in one of the command neurons, the AVD neurons    . The LIMidentity . Howeverression) . These de mutant .unc-42 mutants, as described above. The hlh-34 gene, a bHLH-PAS transcription factor, is exclusively expressed in the AVH neuron throughout the life of the AVH neuron . We used CRISPR/Cas9 to engineer a loss-of-function allele of hlh-34  and loss of expression of several innexin genes  SMD neurons had also been reported to express ceh-24 and require ceh-24 for their correct specification , are also significantly enriched for synaptically connected neurons based on the approach by Arnatkeviciute et al. and NDGE analysis. These UNC-3(+) neurons include the UNC-42(+) command interneurons, but also UNC-42(-) ventral cord motor neurons that are directly innervated by command interneurons. Taken together, one can imagine that the C. elegans connectome can be deconstructed into a series of overlapping groups of interconnected neurons whose interconnectivity is defined by what we propose to call ‘circuit organizer transcription factors’  neuron classes are more highly interconnected than expected from any random set of 15 neuron classes. Intriguingly, several of the factors that collaborate with  neurons . All fived above . Similar neurons . Lastly,factors’ . These func-42 is an example of a relatively widely expressed transcription factor, operating in 15 (of the 118) distinct neuron classes of C. elegans. Taking a whole animal perspective, we carved out three common themes in the function of unc-42 in all these different cell types.Most transcription factors are employed in distinct cell types to exert distinct, cell type-specific functions. unc-42(+) neurons, unc-42 appears to act as a terminal selector of neuronal identity in each neuron type it is expressed in. unc-42 is not required for neuron generation or adoption of panneuronal features, but it initiates their respective terminal differentiation program, as inferred by the requirement of unc-42 for the expression of a host of terminal marker genes of the respective neuron classes. Not every single identity marker is completely affected in unc-42 mutants, likely due to partial compensation by other cooperating terminal selectors. Based on its continuous expression throughout larval and adult stages, UNC-42 likely also maintains the expression of its effector genes, as demonstrated for other terminal selector-type transcription factors  neurons. Moreover, removal of individual unc-42-target genes phenocopies behavioral defects observed upon loss of unc-42, further corroborating the relevance of unc-42 and its targets in controlling neuron function. Based on our binding sites analysis, we furthermore predict that UNC-42 directly controls the expression of terminal effector genes in different neuron types. The identification of unc-42 as a terminal selector in many different neuron types also corroborates the importance of homeobox genes in neuronal identity specification, inferred from past studies of homeobox gene expression and function in C. elegans  is expected to result in fully penetrant and expressive defects. A precedent for such scenario is the TTX-3/CEH-10 heterodimer that cooperative binds to cis-regulatory motifs present in AIY neuron-expressed genes  neurons are synaptically interconnected. This suggests that unc-42 may also have a role in assembling neurons into functional circuitry. Interestingly, the processes of unc-42(+) neurons traverse distinct neighborhoods (‘strata’) of the nerve ring  as well as loss of genes possibly involved in synaptic targeting/synapse formation. Taken together with the effect of unc-42 on neurotransmitter, neurotransmitter receptor, and neuropeptide expression, unc-42 therefore coordinates both circuit assembly and signaling within this circuit. Whether ectopic misexpression of unc-42 is sufficient to recruit such ectopic neurons into the set of unc-42(+) interconnected neurons is an obvious next question, but will require an improvement in available tools to visualize synaptic wiring.The third common theme that emerges from our nervous system-wide analysis of rve ring , indicatunc-42, enriched in synaptically connected neurons. Many of these transcription factors have been shown to be required to control the identity of individual neurons that express these transcription factors, that is, they act as terminal selectors that coordinate the expression of many/most/all terminal identity features of a neuron. Of particular note is the observation that several of the transcription factors that cooperate with unc-42 in subsets of unc-42(+) neurons to specify the identity of specific neurons  are also expressed in synaptically connected sets of neurons. Hence, one can envision that complex circuitry is defined by nest, partially overlapping sets of terminal selector-type transcription factors, each of which define the assembly of groups of neurons into synaptic pathways  and ceh-24(+) neurons  neurons, thereby wiring together originally distinct synaptic pathways. It will be fascinating to assess whether such mechanisms of circuit evolution can be inferred from examining terminal selector expression and synaptic wiring in distantly related nematode species.One way to think about such circuit association is in the context of evolution of neuronal circuitry. Perhaps C. elegans strains used in this study are listed in hlh-34 transgene reporters are expressed exclusively in AVH, not in AVJ. This cell identification was done with specific landmark strains and will be reported elsewhere. It is also consistent with recent scRNA data, which revealed hlh-34 expression exclusively in AVH  were acquired using the Zen software and analyzed using the Zen software or ImageJ. Representative images are shown following orthogonal maximum intensity projection of 2–25 z-stacks.eat-4   (NeuroPAL (otIs696)  , cho-1 (otIs354) , and NeuotIs696) . ExpressFor quantification of axon length shown in For quantification of RAB-3::GFP puncta shown in unc-42 mutant animals were evaluated individually and were not different as compared to wild type animals (data not shown). Additionally, a Euclidean distance was assessed using the distance formula, as shown in For quantification of cell nucleus positions, confocal Z-stacks were opened in the NeuroPAL ID software as described in unc-42(e270) was fixed as previously described (unc-42(e270) was then imaged either manually with a Phillips CM10 TEM or automatically with a JEOL 1400Plus TEM and the SerialEM software. Sections were then aligned and montaged, all of the axons in the nerve ring were serially traced, and synapses were annotated using the TrakEM2 software (unc-42(e270) synapse and axon adjacency counts to the previously described wild type (N2U) (escribed . These fsoftware . The regsoftware . Synapsesoftware . To comppe (N2U) , the secWormTracker assays were conducted and analyzed as previously described . To avoiFor the categorical data shown in https://www.wormwiring.org and described in The probability that a transcription factor is expressed in a set of neurons that are more interconnected than the whole connectome was calculated with a probability mass function using a binomial distribution. Analysis was performed as described  with modk success in n trials is given by the probability mass function:The probability of having C. elegans hermaphrodite connectome, excluding the pharyngeal neurons. This was calculated by examining all possible neuron pairs, excluding interclass pairs, where order matters , and totaling how many of these pairs were connected by either a chemical and/or electrical connection. Both electrical and chemical synapses were doubly counted .We define the ‘probability of success’ (p) as the probability that any two given neurons are connected in the somatic  The ‘number of trials’ (n) was determined by totaling all possible pairs of neurons in which the transcription factor was expressed, excluding interclass pairs, where order matters.The ‘number of successes’ (k) was determined for each transcription factor by totaling how many of these pairs were chemically and/or electrically connected.https://github.com/hobertlab/Berghoff_2021  to guide further research in all organisms.The authors explore how neural circuits are established in Decision letter after peer review:eLife. Your article has been reviewed by 2 peer reviewers, onw of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Piali Sengupta as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "The Prop1-like homeobox gene unc-42 specifies the identity of synaptically connected neurons" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.We would like to draw your attention to changes in our policy on revisions we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, when editors judge that a submitted work as a whole belongs in eLife, either of which would be linked to the original paper.Our expectation is that the authors will eventually carry out the additional experiments and report on how they affect the relevant conclusions either in a preprint on bioRxiv or medRxiv, or if appropriate, as a Research Advance in Summary:C. elegans. They identify a transcription factor, Prop1/Unc-42, present in 15 neuronal classes that are all synaptically connected, and show that this factor coordinately regulates both differentiation and connectivity of these neurons. Analysis of the expression pattern of many other transcription factors reveals a striking relationship between transcription factors and neuronal network. Weaknesses are the minimal statistics showing preferential connectivity, and the functional analysis of connectivity. Strengths are the comprehensive analysis, high quality of the data, and the power of the concept (one factor – one circuit) to guide further research in all organisms.The authors explore how neural circuits are established in Essential revisions:1. The analysis of connectivity within the 15 classes is weak. The UNC-42 neurons are in the head, but comparing them to random neurons throughout the body is not a fair test: the control group should be a similar number of UNC-42-negative neurons in the same region of the head. Data on connectivity from UNC-42+ to UNC-42- neurons should be given; currently it is impossible to tell if there is more connectivity within the group or from the group to the strongest connected UNC-42-negative neurons (or from UNC-42-negative neurons to UNC-42+ neurons). This is the major conclusion of the paper and needs additional analysis to make the conclusions more convincing.2. The behavior should be clarified. It appears unc-42 mutants fail all motor tasks. If they are specifically poor in nociceptive escape tasks that should be made clear. Documenting behavioral specificity would help support the specificity of the UNC-42 circuit. That is, does UNC-42 generate a specific behavior (via its downstream circuit) or does UNC-42 simply eliminate motor function?3. Figure 3: There is considerable variation in penetrance and expressivity between different neuron types regarding the phenotype (loss of cholinergic and glutamatergic transmitter markers) of unc-42 mutants. Yet the cartoon displays these effects as complete, which would seem to be an exaggeration. Also, why would there be such variability in the phenotype between cell types? Wouldn't "master terminal selectors" show complete penetrance and expressivity?4. Do UNC-42+ neurons share a common neuropil target? Do they share a common pathfinding intermediate ? Common targeting features would help support a common molecular pathway with UNC-42 at the top. The opposite is interesting too – perhaps UNC-42 regulates different pathfinding gene batteries just like it regulates different neurotransmitter biosynthetic enzymes – but it would be good for the reader to be given this information.5. It seems unfair to attribute whole animal mutant phenotypes  to the UNC-42 circuit. Or am I missing something: were these neuron-specific experiments? If the UNC-42 phenotype is severe  then how relevant are phenocopies? Anything to strengthen this section would help the paper.Drosophila lamina neurons, where loss of the CAM dip-beta does not remove synapses, but rather it is required to restrict subcellular localization (thus mutants have ectopic synapses) .6. It seems the TEM analysis – impressive though it is – is not properly analyzed or discussed. It is true that the SAAVL > AVAL data strongly support the idea that proximity is not sufficient for connectivity, but some of the neurons show different results, such as increased connectivity in the mutant, rather than decreased. This needs to be noted in the paper. Also, it could be discussed in the context of synaptic choice in eLife. Your article has been reviewed by 3 peer reviewers, including Chris Q Doe as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Piali Sengupta as the Senior Editor.Thank you for submitting your article "The Prop1-like homeobox gene unc-42 specifies the identity of synaptically connected neurons" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:These are all text or figure changes. No experiments are required. Yet the comments are important to improve the clarity and readability of the paper.1. Line 139 says (REFs). Need to add the references.2. Line 173-175 says 17 additional HD transcription factors (in addition to Unc-42) show common connectivity. This should be documented in the Results section with the names of the TFs and the statistics on connectivity. Perhaps a supplemental table listing all 18 HD TFs that fall in this category. The discussion should be expanded to discuss what these 18 HD TFs have in common that may distinguish them from the other 65 HD TFs that don't have common connectivity.3. The legend to Figure 1 mentions panel F with NDGE analysis. But there is no panel F in Figure 1. Please add.4. The authors claim that mild effects (variability/penetrance/expressivity) is common for "terminal selectors", which were originally defined as "controlling all aspects of a specific neuron's cell specific gene expression", "during development and into adults". How mild can the effects be then, to still allow for the "terminal selector" definition to be used for a TF.And the role of "terminal selectors" is compensated by "cofactors", which are also "terminal selectors"? Or perhaps merely "late acting, partially important, cell fate determinants"?5. Lines 482-483, 526-545, 562. The original definition of "terminal selectors' was that they should control "all sub-type defining genes". But now the authors claim that this is a "grey zone", and that 19/20 (che-1) or 37/40 (unc-3) targets is sufficient. So what is the percentage of sub-type defining genes that a TF needs to regulate to qualify as a "terminal selector, 95%, 90%?6. The authors did not disclose the nature of unc-42(e270), which was used in ultrastructural analysis and only one allele unc-42(e419) was used throughout the entire study. Please acknowledge in the paper, or correct the text to show other alleles.7. Some data  are presented in a crowded and nearly invisible manner, diminishing the value to any readers. Essential revisions:1. The analysis of connectivity within the 15 classes is weak. The UNC-42 neurons are in the head, but comparing them to random neurons throughout the body is not a fair test: the control group should be a similar number of UNC-42-negative neurons in the same region of the head. Data on connectivity from UNC-42+ to UNC-42- neurons should be given; currently it is impossible to tell if there is more connectivity within the group or from the group to the strongest connected UNC-42-negative neurons (or from UNC-42-negative neurons to UNC-42+ neurons). This is the major conclusion of the paper and needs additional analysis to make the conclusions more convincing.In addition to the analysis that we originally presented (and re-worded for clarity in the revised version), we now added an entirely novel set of statistical analysis that assesses the extent of interconnectivity of unc-42-expressing neuron. This analysis further corroborates that unc-42 indeed defines a set of neurons that are more interconnected than expected by chance and is presented on page 6 of the manuscript. This analysis was conducted by a new author on the manuscript who conducted a similar type of analysis on recently released scRNA data.2. The behavior should be clarified. It appears unc-42 mutants fail all motor tasks. If they are specifically poor in nociceptive escape tasks that should be made clear. Documenting behavioral specificity would help support the specificity of the UNC-42 circuit. That is, does UNC-42 generate a specific behavior (via its downstream circuit) or does UNC-42 simply eliminate motor function?We regret that we were not clearer about this. The reviewer would be totally correct in pointing out that loss of the nociceptive escape behavior would have little meaning if unc-42 animals were simply totally immobile, failing all motor tasks. But, no, this is not the case, unc-42 mutants do not simply fail all motor tasks; they are fine in plenty. We now document this properly in a new Supp Table S3 in which we list all locomotory features that we quantified and we refer to this in the main text.3. Figure 3: There is considerable variation in penetrance and expressivity between different neuron types regarding the phenotype (loss of cholinergic and glutamatergic transmitter markers) of unc-42 mutants. Yet the cartoon displays these effects as complete, which would seem to be an exaggeration. Also, why would there be such variability in the phenotype between cell types? Wouldn't "master terminal selectors" show complete penetrance and expressivity?We felt that the visualization of partial effects would have made the cartoons (that we use throughout the manuscript) too complex. Note that in many of the cartoon we also need to use multiple color. Introducing an additional level of information for partial effects (eg shading or stippling) would beat the purpose of the schematic. We now indicate in the figure legends that a loss of color indicates the existence of an effect on marker gene expression, irrespective of whether the effect is fully penetrant or not.unc-42 and unc-3 in command interneurons , we now similar synergistic effects in three other neuron types, with yet different cofactors: with hlh-34 in AVH and with lim-4 in RMF and RMH. The data is shown in Figure 3 (for lim-4) and Figure 13 (for hlh-14). We have updated the summary figure 14 as well.In terms of variability/penetrance/expressivity – the literature shows this to be a common feature of loss of transcription factors, including terminal selectors. This partial penetrance has, in a great number of cases, shown to be due to cofactors that can partially compensate for loss of the TF. Such cofactors are different in different cell types and, hence, the extent of the phenotype may differ from cell type to cell type. In the original version of the manuscript, we had only considered a few co-factors, but in the revised version, we have significantly expanded this cofactor theme: While in the original version we had only shown synergistic effects of 4. Do UNC-42+ neurons share a common neuropil target? Do they share a common pathfinding intermediate ? Common targeting features would help support a common molecular pathway with UNC-42 at the top. The opposite is interesting too – perhaps UNC-42 regulates different pathfinding gene batteries just like it regulates different neurotransmitter biosynthetic enzymes – but it would be good for the reader to be given this information.Yes, same neuropil target. We now illustrate this in a new 3D rendering, added to Figure 1.5. It seems unfair to attribute whole animal mutant phenotypes  to the UNC-42 circuit. Or am I missing something: were these neuron-specific experiments? If the UNC-42 phenotype is severe  then how relevant are phenocopies? Anything to strengthen this section would help the paper.Yes, this indeed needs clarification. As stated above, unc-42 mutants do not have all motor behaviors affected. And, no, the mutants were not neuron-specific removals. As such the phenocopies come, of course, with caveats. We consider them not proof of direct relationship, but rather a necessary precondition to consider them good candidates for conferring the unc-42 defects. Not more, not less. We now clarify this in the text (p.15).Drosophila lamina neurons, where loss of the CAM dip-beta does not remove synapses, but rather it is required to restrict subcellular localization (thus mutants have ectopic synapses) .6. It seems the TEM analysis – impressive though it is – is not properly analyzed or discussed. It is true that the SAAVL > AVAL data strongly support the idea that proximity is not sufficient for connectivity, but some of the neurons show different results, such as increased connectivity in the mutant, rather than decreased. This needs to be noted in the paper. Also, it could be discussed in the context of synaptic choice in We are a little reluctant to highlight the relatively modest increases in some connection. In contrast to some of the losses, the increases seem to be in the range of ~2fold, which is more in line with the normal animal to animal variability that one observes. It’s totally possible that this is real, but we do not want to sound like we try to overinterpret our data.Essential revisions:These are all text or figure changes. No experiments are required. Yet the comments are important to improve the clarity and readability of the paper.1. Line 139 says (REFs). Need to add the references.Fixed.2. Line 173-175 says 17 additional HD TFs (in addition to Unc-42) show common connectivity. This should be documented in the Results section with the names of the TFs and the statistics on connectivity. Perhaps a supplemental table listing all 18 HD TFs that fall in this category. The discussion should be expanded to discuss what these 18 HD TFs have in common that may distinguish them from the other 65 HD TFs that don't have common connectivity.Apologies for this oversight. It’s now in Figure 1F and in a new Supplementary File 2.We actually cut this number down to 8 by introducing the criterion that BOTH statistical methods that use have to show enrichment (before we only used either one). It’s more conservative.In regard to what those genes have in common in comparison to the other TFs, we are at a loss to explain it. Perhaps a reflection of those being the most ancient TFs to have become recruited into this function, but that’s fantasy.3. The legend to Figure 1 mentions panel F with NDGE analysis. But there is no panel F in Figure 1. Please add.Apologies, done (as stated above).4. The authors claim that mild effects (variability/penetrance/expressivity) is common for "terminal selectors", which were originally defined as "controlling all aspects of a specific neuron's cell specific gene expression", "during development and into adults". How mild can the effects be then, to still allow for the "terminal selector" definition to be used for a TF.The definition of a defect – no matter whether a marker is completely off or off in some animal  or less strongly expressed  – is “any defect” matters, as long as it statistically significant of course. The extent of defects differ by factor/target/cell not based on any real conceptual differences, but based on mere enhancer architecture: In those cases where we know that multiple factors bind in a cooperative manner to target DNA, the effect of removal of either factor is completely penetrant and expressive (example: AIY neuron – ttx-3/ceh-10 or touch neurons – unc-86/mec-3). In other case, terminal selectors work more in a “billboard” type of mechanisms, where it is the additive, non-coperative binding of multiple factors that leads to full target gene activation (example: dopamine neurons – ast-1/ceh-43/ceh-20) – in such case, removal of a single factor can be partially compensated for by the other factors.And the role of "terminal selectors" is compensated by "cofactors", which are also "terminal selectors"? Or perhaps merely "late acting, partially important, cell fate determinants"?They would also be terminal selectors.Overall thee are really good points and are glad to have been prompted to clarify this. The above responses are now added into an additional paragraph in the Discussion.5. Lines 482-483, 526-545, 562. The original definition of "terminal selectors' was that they should control "all sub-type defining genes". But now the authors claim that this is a "grey zone", and that 19/20 (che-1) or 37/40 (unc-3) targets is sufficient. So what is the percentage of sub-type defining genes that a TF needs to regulate to qualify as a "terminal selector, 95%, 90%?This is a good question and hard to answer definitively. What’s notable is that empirically, there are very few cases that lie in the middle. Either a TF affects are large majority of markers, or it affects very few (we comprehensively have listed this in a WIRES review in 2016). The accompanying paper that analyses the occurance of terminal selector binding sites takes a more quantitative stab at this problem: If there are more binding sites of TF in the complete battery of neuron-type specific genes (scRNA) than expected by chance, then we count it as a terminal selector.6. The authors did not disclose the nature of unc-42(e270), which was used in ultrastructural analysis and only one allele unc-42(e419) was used throughout the entire study. Please acknowledge in the paper, or correct the text to show other alleles.Good catch. The preparation for the EM analysis (i.e. fixing and staining) was done on e270, before the molecular identity of unc-42 was known. e270 is a missense mutation in a conserved homeodomain residue, e419 is a premature stop in the homeodomain. Now stated in paper.7. Some data  are presented in a crowded and nearly invisible manner, diminishing the value to any readers.Since those are online-only, they can be blown up. The are in vector-based AI format, so there is no loss of resolution when blown up.


The ongoing SARS-CoV-2 pandemic has tested the capabilities of public health and scientific community. Since the dawn of the twenty-first century, viruses have caused several outbreaks, with coronaviruses being responsible for 2: SARS-CoV in 2007 and MERS-CoV in 2013. As the border between wildlife and the urban population continue to shrink, it is highly likely that zoonotic viruses may emerge more frequently. Furthermore, it has been shown repeatedly that these viruses are able to efficiently evade the innate immune system through various strategies. The strong and abundant antiviral innate immunity evasion strategies shown by SARS-CoV-2 has laid out shortcomings in our approach to quickly identify and modulate these mechanisms. It is thus imperative that there be a systematic framework for the study of the immune evasion strategies of these viruses, to guide development of therapeutics and curtail transmission. In this review, we first provide a brief overview of general viral evasion strategies against the innate immune system. Then, we utilize SARS-CoV-2 as a case study to highlight the methods used to identify the mechanisms of innate immune evasion, and pinpoint the shortcomings in the current paradigm with its focus on overexpression and protein-protein interactions. Finally, we provide a recommendation for future work to unravel viral innate immune evasion strategies and suitable methods to aid in the study of virus-host interactions. The insights provided from this review may then be applied to other viruses with outbreak potential to remain ahead in the arms race against viral diseases. Seasonal strains of Influenza and periodic epi/pandemics, such as the latest SARS-CoV-2 pandemic are a grave concern for public health. With our developments encroaching into natural habitats, it is unavoidable that the barrier between reservoir hosts for viruses and the human population is slowly eroded, increasing risk of emerging zoonotic viruses . This isvia various pattern recognition receptors (PRRs). For example, viral RNA is recognized by Toll-like receptors  and RIG-I-like receptors (RLRs), while foreign DNA is recognized by cytosolic DNA sensors . The activation of innate immune sensors triggers a signaling cascade ultimately leading to the induction of type I and/or type III IFNs. The type I IFN (consists mainly of IFNα/β) binds to IFNα receptors 1 and 2 (IFNAR1/2) and type III IFN  binds to IFNλR/IL-10Rβ, activating expression of hundreds of ISGs to inhibit the viral replication cycle. Many studies have also shown the potency of IFN pretreatment prior to viral infection in inhibiting viral replication  efficiently inhibits viral replication through production of type I/III interferons (IFNs) and their respective interferon stimulated genes (ISGs). The unique molecular patterns of viruses are detected in host cells lication . Howeverlication . The dellication . This hade novo identification  and virus-host interaction studies .With the ever-looming threat of the next pandemic, understanding how viruses evade the immune response may allow us to devise novel antiviral treatments and strategies, or repurpose existing drugs as a rapid countermeasure to emerging threats; especially with a monumental case study such as the SARS-CoV-2. Furthermore, identifying the viral genes required for host immune suppression may aid in the development of a recombinant virus with key deletions as a vaccine candidate. Recent developments in methodologies have allowed for higher throughput analyses to be performed, providing new tools for In this review, we first provide a brief overview of general evasion strategies against the innate immune system. Then, we utilize SARS-CoV-2 as a case study to highlight the methods used to identify the mechanisms of innate immune evasion. Finally, we provide a recommendation for future work to unravel the innate immune evasion strategies by viruses, and additional methods to aid in the study of virus-host interactions. The insights provided from this review may then be applied to other viruses with outbreak potential to remain ahead in the arms race against viral diseases.in bold.Viral evasion of the innate immune system can be broadly summarized into a few categories: (a) interference of host pathogen sensors and antiviral factors, usually affecting the type I (IFNα/β) and/or type III (IFNλ) interferon signaling pathways, (b) modification of 5′-end of viral mRNA, and (c) formation of replication organelles. Some examples of common viruses are given, while SARS-CoV-2 will be covered in the next section. Methods used for identification of viral-host interactions in each study will be included in parenthesis The viral genome consists of structural, non-structural, and accessory proteins. These proteins, and even viral RNA, can perturb the innate immune response in the host cell. Below are examples of each class of molecules interfering with the function of the innate immune system, leading to viral evasion.ε complex, thereby interfering with the activation of the type I IFNs (Co-Immunoprecipitation). Influenza M1 protein has been found to interact with C1qA of the complement system, inhibiting its interaction with IgG, thereby protecting the Influenza virus from complement mediated neutralization in vitro .SARS-CoV M protein has been found to interfere with formation of the TRAF3.TANK.TBK1/IKKe I IFNs  .Influenza NS1, perhaps a prime example of innate immune evasion , perturbImmunoprecipitation-Mass Spectrometry [MS]). Influenza A PB1-F2 has been shown to inhibit interferon induction downstream of the pattern recognition receptor pathway, RIG-I-TRIM25, by interacting with MAVS .MERS-CoV ORF8b interferes with the interaction of IKKϵ and HSP70-1A by competing with IKKϵ for HSP70-1A, preventing signaling through the IRF3 pathway from proceeding, thereby inhibiting the production of IFNβ  (Immunopith MAVS  (FunctioRNA-Immunoprecipitation).DENV (Dengue virus) subgenomic flavivirus RNA is known to interfere with the innate immune system through its direct interactions with TRIM25 and interfering with its deubiquitylation, thus interfering with the RIG-I signaling and consequently, type I IFN production  .Influenza has been known to incorporate CD59 into the membrane of the virion, allowing it to inhibit the formation of the membrane attack complex by the complement system   .Influenza viruses have been known to engage in a process known as “cap snatching.” Viral RNA bound RNA-dependent RNA polymerase (RdRp) associates with the C terminal domain of RNA polymerase II, allowing interaction of polymerase basic protein 2 (of RdRp) with the 5′ cap of host RNA. Host RNA is then cleaved 10–13 nucleotides down, producing a capped oligonucleotide that is used to prime viral RNA transcription  (FunctioScreens) . The polScreens) . NSP16 oScreens)   and invaginations, are appropriated intracellular membranes that may, speculatively, shield viral PAMPs from the innate immune sensors present within the cytoplasm . These sImmunofluorescence Assay, RT-qPCR). It has, however, been shown that at least in coxsackievirus (an enterovirus), replication organelles do not seem to result in enhanced innate immune evasion . With diverse observations, the impact of replication organelles on innate immune evasion may be unique to each viral infection and mechanisms behind this phenomenon are still relatively unclear, requiring further research for each virus of interest.DENV, for example, conceals its dsRNA within DMVs, reportedly diminishing the impact of the host innate immunity (as determined by IFNβ expression), as compared to Japanese encephalitis virus, whose dsRNA is detectable in the cytoplasm much earlier than DENV  , spike (S), envelope (E), membrane (M), and nucleocapsid (N)-3′ genes. The ORF1ab polyprotein is comprised of 16 NSPs , but ORF10 was not detected . AnotherAs with all newly emerging pathogen, our understanding of how SARS-CoV-2 evades the immune system, and the functional roles of its genes are limited. Gene overexpression studies are commonly performed to further characterize genes of unknown functions . In suchSeveral studies have utilized IFNβ-promoter firefly luciferase reporter assay as a readout of IFN suppression to screen for IFN antagonists. A study by Taken together, the overexpression of at least NSP1, NSP3, NSP11, NSP12, NSP13, NSP14, NSP15, ORF3, ORF6, ORF8, ORF9b, ORF10, N, and M have been implicated to antagonize IFN induction, though these results were not consistent across studies. In a study by It is expected that more proteins could play a role in viral innate immune evasion owing to the large genome size of SARS-CoV-2 and the presence of numerous non-canonical transcripts with unknown function. Overexpression, while with its caveats, is a relatively simple and quick approach as a first line of screening to search for viral antagonists for antiviral factors.via promoting K48 ubiquitination , protein-protein interaction (PPI) studies are necessary to determine the host factor involved and the pathway affected. Comprehensive PPI maps using AP-MS have been performed by tination . The SARtination . An impoAs an RNA virus with a relatively large genome (∼30 kb) and multiple subgenomic RNAs, it is expected that various RNA-RNA interactions may exist between the virus and host. Indeed, a comprehensive mapping of RNA-RNA interactions in infected Vero E6 cells revealed ∼300 host RNAs that interact with the SARS-CoV-2 genomes, with mitochondrial RNAs and snoRNAs being strong interactors . The autCurrent methods of investigating host-viral interactions rely greatly on overexpression, such as luciferase reporter screens or single protein overexpression followed by pull-down to identify PPIs. As discussed in the previous section, the overexpression of viral proteins may lead to false positive findings due to the artificially elevated levels of viral proteins not found in normal infection. Viruses, utilizing their repertoire of DNA/RNA and proteins from their small genome, adapted multiple means of subverting the innate immune response to ensure their replication at the detriment of the host. The identification of these mechanisms is important to devise strategies to dampen the virulence of a virus and prevent severe infection and loss of life during an outbreak. Thus, future studies should move toward the use of whole virus and biologically relevant cell systems to elucidate the multipronged strategies employed by viruses to evade the innate immune system.Reverse genetics (RG) is a powerful method which allows the study of viral proteins in the whole virus context which more accurately reflects the virus-host interactions during normal infection. The method utilizes an infectious clone generated from full-length cDNA of the virus and allows mutagenesis to be performed to investigate the functional roles of certain genes of interest. Many groups have developed RG systems for SARS-CoV-2, with some safe for use in Biosafety Level 2 laboratories, opening SARS-CoV-2 related studies to more researchers . Howeverex vivo) grown in 3D air-liquid interface cultures have been shown to exhibit the anatomical and physiological processes found in vivo  it originates from monkeys, and (ii) it is known to lack type I IFN genes , which makes it difficult to resolve the complexity of host innate immune responses to SARS-CoV-2 in humans . Other c in vivo  and coul tissues . As prim tissues . Recent  tissues . Further tissues . This ca tissues .In terms of human viral infection, protein-protein interaction between viral and host proteins remains the mainstay of where we identify viral innate immune evasion mechanisms. To study the large permutation of interaction between viral and host proteins, high-throughput methods followed by targeted validation are the main methods widely used to elucidate such interactions.In silico methods are mostly based on the mRNA sequence, structural similarity, and phylogeny and can be used to predict interaction between viral proteins and host proteins These methods can be used to guide verification with in vivo and in vitro methods. In vitro methods can be further categorized into targeted and non-targeted methods. In non-targeted methods, a general screen is done to identify all possible interaction pairs in a set of proteins, which in the case of viral-host interaction studies can be performed on the cell lysate of infected cells. In targeted methods, a protein of interest (bait) is expressed and used as the focal point to identify all PPIs with that protein. In vivo methods mainly make use of two-hybrid systems in simple model organisms. Two-hybrid systems are usually based in yeast, where interaction between proteins (one bound to a DNA-binding domain and the other to an activation domain) recombinantly expressed in the yeast host is required for reporter gene expression , tandem AP, and proximity labeling. Co-immunoprecipitation utilizes immobilized antibodies on beads/surfaces against a protein of interest (bait). The infected cell lysate/protein cocktail is then allowed to interact with the beads/surface, resulting in the binding of the bait to the immobilized antibody. With a robust interaction between the bait and any prey (proteins that are able to interact with the bait), the bait-prey complex will remain associated with the immobilized antibody when the non-specific proteins are washed off, leaving the bait-prey complex bound to the beads . FurtherProximity dependent labeling is based on labeling proteins in close proximity to the protein of interest. This method is useful for determining transient interactions in the protein interactome, as the extensive washing steps required to eliminate non-specific proteins for AP and co-immunoprecipitation may result in the destabilization of such transient interactions. BioID, the first proximity labeling strategy, is based on BirA, a biotin ligase that has been adapted to biotinylate proteins in close proximity (∼10 nm) upon exposure to biotin and ATP . The bioNon-targeted methods include crosslinking investigations, which are based on the premise of forming covalent bonds between amino acid residues that are in proximity. The parameters of the crosslink  depend heavily on the crosslinker used, with each having its own set of advantages and disadvantages. Crosslinking is followed by purification of crosslinked proteins and finally identification by MS .While viral-host RNA-RNA interaction is uncommon in mammalian viruses, the advent of RNA-RNA interaction platforms can serve to uncover novel interaction at the RNA levels between virus and host. For example, studies of small RNA plant viruses have shed light on RNA silencing . Much woin vivo) (in situ conformation sequencing)  , PARIS , 2018, Sin vivo)  and RIC-uencing)  are someThese methods follow a general framework. Psolaren or one of its derivatives, AMT, is used to crosslink interacting RNAs. In context, infected cell lysate/an infected cell can be used to pinpoint viral-host RNA interactions. This is followed by a purification step, such as gel purification, to isolate the crosslinked interacting RNA molecules. Each individual interacting RNA duplex is then subjected to proximity ligation to ensure that their interaction is preserved. Interacting complexes are then isolated before the crosslink is reversed, releasing both RNAs (though they remain associated due to proximity ligation). This preserved interaction allows sequencing methods, such as PORE-cupine  , to pinpThese methods are applicable to both Viral (Protein)—Host (RNA) and Viral (RNA)—Host (Protein) interactions. The methods may be divided into RNA-targeted (using RNA as bait) and protein-targeted (using protein as bait).For RNA-targeted methods, they share a commonality in that a tag is expressed on in vitro transcribed RNA, or a probe is bound to the RNA of interest. This tag, whether biotin  or an apThese methods can be further differentiated by the need for a crosslinker. Crosslinkers commonly used in RNA-protein interaction studies are UV light  and formin vivo biotin-tagged RAP) (A range of methods are available for exploitation: RAP (RNA antisense purification) , PAIR p, MS2-Bioged RAP) , TRIP (tged RAP) , ChIRP (ged RAP) , CHART (ged RAP)  and VIR-ged RAP) .One method that does not require crosslinking makes use of proximity labeling instead. RaPID (RNA-protein interaction detection)  utilizesFor protein-targeted methods, CLIP (crosslinking and immunoprecipitation) can be utilized . Interacvia high-throughput sequencing  can be further investigated for impact on the innate immune response by perturbing and/or enhancing them. Pathogen sensors, IFN and ISG expressions are some of the metrics that can be used to approximate the impact of the interactions.In conclusion, the emergence of novel viruses like SARS-CoV-2 is an inevitability with the constantly expanding global population. The COVID-19 pandemic has demonstrated the lethality of such emerging pathogens which we have limited information about and the impact that they can have on our globalized society. Identifying viral evasion strategies is, thus, an important component of viral research to guide the development of therapeutics and halt transmission within the population, for both emerging and seasonal viruses. There are overlapping and common viral evasion strategies which provide a starting point to uncover these mechanisms and identify viral/host factors involved. From the studies reviewed in this paper, we see that the focus of the viral-host interactions studied are ones that have some form of homology to related viruses with known effect on the innate immunity. Furthermore, the focus seems fixated on overexpression studies (which is not representative of whole virus infection) and protein-protein interactions, with a lack of studies focusing on the RNA-RNA and RNA-protein interactions that emerging viruses may have. Here, by consolidating the current studies on SARS-CoV-2, a virus with strong antiviral evasion capabilities, we have identified areas that require integration of new approaches  to identify biologically relevant viral factors that can be targeted for management of viral infections (summarized in DT, ZL, and KT contributed to the initial conceptualization of the manuscript and writing of the manuscript. DT and ZL contributed to literature search. DT, ZL, KT, and JC contributed to literature selection, review, and finalization of the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


As recent trends in policymaking call for increased contributions from behavioral science, nudging and boosting represent two effective and relatively economic approaches for influencing choice behavior. They utilize concepts from behavioral economics to affect agents’ concurrent suboptimal choices: in principle, without applying coercion. However, most choice situations involve some coercive elements. This study features a functional analysis of rationality, nudging, and boosting applied to public policy. The relationship between behavior and environmental variables is termed a “behavioral contingency,” and the analysis can include social and cultural phenomena by applying a selectionist perspective. Principles of behavioral control, whether tight or loose, may be exerted by policymakers or regulators who subscribe to paternalistic principles and may be met with demands of libertarianism among their recipients. This warrants discussion of the legitimacy and likelihood of behavioral control and influence on choices. Cases and examples are provided for extending the unit of analysis of choice behavior to achieve outcomes regulated by policies at the individual and group levels, including health, climate, and education. Further research and intervention comprise the study of macrocontingencies and metacontingencies. Advancing the understanding and application of behavioral science to policymaking may, therefore, benefit from moving from the relatively independent contributions of behavioral economics and behavior analysis to an inclusive selectionist approach for addressing choice behavior and cultural practices. Governments are increasingly resorting to behavioral science for addressing their policy objectives . Yet, what is rational for one agent may not be rational for another, or for the group to which they belong.Finally, some ethical considerations of behavioral influence and control are discussed, before concluding with an outline of practical implications for behavioral designers and policymakers. These implications affect macrocontingencies and metacontingencies, which identify the relations of arranging the environmental and social contingencies of behavior in larger groups and cultures, respectively. According to Taleb , “What ieconomic behavior corresponds to the behavioral repertoire that is composed of (1) the allocation of scarce resources by Simon  outlinesby Simon . The demace 1814/ precededLaplace never called it a demon, but with this archetype of a superhuman powered by infinite computing capacities, economic behavior is always rational and bears the most beneficial consequences for the agent. Laplace’s demon is impossible, given the principle of computational irreducibility. A computer that could follow and predict everything in the universe would need to be as big as that universe; thus, models that approximate are the best that can be achieved.utility in economics has changed since its first formulation in terms of hedonism by moral philosophers Jeremy Bentham (1748–1832) and John Stuart Mill (1806–1873). However, it remains mostly an interdependent measure. If an individual or a group act to gain more utility for themselves or their group, this may directly or indirectly imply that contingencies may be altered in a way that lowers the utility of another individual or group through the former’s cumulative behavior and its economic consequences. For example, if going to the park is preferred to going to the mall on a sunny weekend, and this difference in utility is shared among the larger community, it follows that going to the park may not entail the same pleasure for everyone. If the community has access to only one park, there might not be enough personal space for everyone to make it either worthwhile or an optimal choice, which in the present example represents a common-pool resource. According to theories of rational choice, however, rational agents can predict the crowds in the park and calculate their loss of comfort: they avoid the park and optimize their utility, regardless of the other agents’ utilities. The interrelation between agent’s and others’ choices is typically omitted in models of rational choice that are concerned with the individual unit of analysis. Nevertheless, the behavior of utility optimizers is affected by selfish concerns, not by the utility of other agents. This discrepancy represents a social dilemma  and at Another selecting contingency is given by the generalized conditioned reinforcers: money represents the example to which we may most easily relate Skinner, . BecauseThe matching law , Herrnstein and Prelec . However, Glenn .r, Glenn , p. 18.Interventions based on behavioral science may contribute in an impactful and timely fashion toward increasing environment-conscious choice behavior, among other possible applications. The data may lay the foundations for developing better-informed and evidence-based policies for larger groups and communities, improving sustainability for both behavioral- and policy-level interventions. It is possible to leave the aspect of interaction  out of the analysis: this choice of method is certainly more economic, but less desirable, for it may limit users’ involvement because of their interdependence.metabehavior, which identifies the behavioral class of cultural practices  knows best what constitutes a good outcome for somebody else than they do themselves, and so should act to make this come about, even without their consent. A “libertarian” form of paternalism softens this position by removing coercion and allowing the receiver of the paternalistic act to change the course of action. The task of defining a nudge has attracted increasing interest from several disciplines, and many formulations are available: from an attempt at influencing judgment or choice by cognitive exploitation Hansen,  to subjeNudges exploit contextual information to alter the likelihood of responding in line with the designer’s intentions or preferences. Similar to the menu, which represents a subset and a specific arrangement of the physical environment described by Skinner e.g., , choice Cesareo  maintainBecause there is a mutual interaction between behavioral contingencies and an agent’s learning history, but also biological conditions and stimulus situations . In another study by Hallsworth et al.  overtakes the analytical cognitive processing, and the designed controlling environmental contingencies fade into the background of our habitual choice architecture. Contextual considerations and analyses are critical for making meaningful contributions to social policy, and nudges can be useful to achieve the desired results if they can be readily implemented. For example, Fishbane et al.  found thIt is incredibly difficult to solve some of the contemporary (super-)wicked problems  despite the efforts of the top behavioral scientists and using the best behavioral models that are available. Nevertheless, it seems that BA has not yet contributed enough to this mission, although the concepts of macrocontingency and macrobehavior were developed precisely to account for the complexity involved. For example, the work of Embry and Biglan reported by Wilson et al.  consistenonlinear behavior analysis to reach beyond the descriptive linear logic of traditional functional analyses. It includes an analysis of different relationships between contingencies of alternative response patterns rationality of behavior: according to Ruggeri et al. , “BehaviAs the consequences of one agent’s choices affect the choices of other agents, the effectiveness of  nudging interventions can be regarded as the product of cumulative and interlocked choices at the policymaking level, which warrants the analysis of macro- and metacontingencies. If the choice environment is not explicitly designed, whether an agent’s choice behavior is rational or not may be maintained after its first spontaneous or elicited occurrence by the traits of the cultural setting. Hence, rational choice may be regarded as instruction-governed behavior or as environmentally or culturally shaped, regardless of the instruction. For example, federal interventions for reducing greenhouse gas emissions and fighting climate change  or educate agents towards more sensible outcomes . In terms of return on investment, the costs and savings of behaviorally informed policymaking outweighs traditional policymaking ; however, the former does not comprise a universal replacement for the latter and may rather comprise an efficient alternative  and BA. The former rests on the libertarian approach to freedom of choice and personal responsibility, whereas the latter takes a deterministic stance and denies their possibility according to radical behaviorism. Moreover, the liberal take of Rakos  and the Define, Diagnose, Design, Test; Ideas42, Similar to studies of delay discounting, forthcoming experimental efforts should address the relation between magnitude and delay of rewards. Although nudges represent “means of bringing behavior under the control of wide and abstract reinforcer contingencies” Rachlin, , p. 198,Cognitive biases are systematic deviations from instances of rational choice: their meaning and role are entwined with some definitions of nudging, although they formally preceded the debate of whether biases should be considered motives for nudging. The same may be stated about heuristics, which represent cognitive shortcuts that work well most of the time, or else they would not have survived throughout both our phylogenesis and ontogenesis. Although they have not been formally addressed in this study, heuristics are the product of the selection process of an agent’s learning history or, by extension, of his or her reference group. Whether a choice is perceived as right or wrong, or whether the feedback of a certain course of action is not transparent, erroneous heuristics and biases may prevail and be transmitted. However, according to a post-Skinnerian account of language and cognition, a bias represents “a product of our processes of symbolic derivations that are contextually controlled and that occasion verbally controlled behavior” (Tagliabue et al., Another avenue of further research and collaboration includes behavioral decision research, which has greatly influenced the making of BE has been further advanced thanks to the innovative methods and findings typical of decision neuroscience. The relatively new field of neuroeconomics is the result of this synthesis, establishing a neuroscientific account of the interplay between cognition and affect, and automatic and controlled processes of choice (Camerer et al., Whereas macrocontingencies are limited to collective responses that may incidentally put groups in contact with the sum of individual consequences, metacontingencies “focus on the selection of coordinated responses that enable groups to achieve shared goals” Couto, , p. 8; t