Caenorhabditis elegans from Salmonella Typhimurium DT104 infection by Lactobacillus zeae LB1. However, the mechanism is not fully understood. C. elegans exhibits behavior plasticity when presented with diverse pathogenic or commensal bacteria. Whether it can exert approach avoidance to S. Typhimurium through altering its neurological activity remains to be determined. In the current study, both the wild type and mutants defective in serotonin or dopamine production of C. elegans were used to investigate olfactory preference of the nematode to L. zeae LB1, DT104, and Escherichia coli OP50 by choice assays, and its resistance to DT104 infection and the protection offered by L. zeae LB1 using a life-span assay. The expression of target genes in C. elegans was also examined by real-time quantitative PCR. Results showed that pre-exposure to L. zeae LB1 did not elicit aversive olfactory behavior of the nematode toward DT104. Both mutants tph-1 and cat-2 succumbed faster than the wild type when infected with DT104. While pre-exposure to L. zeae LB1 significantly increased the survival of both the wild type and mutant tph-1, it provided no protection to mutant cat-2. Supplementation of dopamine resulted in both the resistance of mutant cat-2 to S. Typhimurium infection and the protection from L. zeae LB1 to the same mutant. Gene expression data also supported the observations in the life-span assay. These results suggest that both serotonin and dopamine play a positive role in the host defense of C. elegans to S. Typhimurium infection and that the L. zeae LB1 protection is not dependent on modifying olfactory preference of the nematode but mediated by dopamine that may have involved the regulation of p38-mitogen-activated protein kinase and insulin/insulin-like growth factor signaling pathways.Salmonellosis is a common foodborne disease. We previously reported the protection of  Salmonella enteritidis infection  worms are significantly more likely than dopamine defective mutants to learn to make conditioned responses linking reward to location. However, little is known about the approach avoidance of C. elegans to Salmonella Typhimurium through altering the neurobehavior that is mediated by neurotransmitters.Schultz, . DysfuncSchultz, . The dop Wheeler  have revC. elegans has been shown to negatively regulate the innate immune response through a D1-like dopamine receptor, DOP-4, by down-regulating the p38/PMK-1 MAPK pathway, thus making the nematode more susceptible to Pseudomonas aeruginosa infection  pathways to control the production of antimicrobial peptides and defensing molecules , and mutant tph-1  were obtained from Caenorhabditis Genetics Center  and cultivated as described  per milliliter was used as food for the nematode. Salmonella enterica serovar Typhimurium DT104 strain SA970934 is a porcine multiantibiotic-resistant isolate  in 1 L of the solution, a concentration of 108 CFU/ml of cell suspension of the pathogen was used in assays. Lactobacillus zeae LB1 was cultured in de Man Rogosa Sharpe (MRS) broth or agar at 37°C for 18 h in an anaerobic chamber  with an atmosphere of 85% N2, 10% CO2, and 5% H2  was spotted onto one side of a new NGM plate and air-dried for 30 min at 25°C. Worms at L4 stage (50–100 worms) that had been washed twice in S basal buffer were then placed at the center of the plate, equidistant from the tested bacterial spots. The nematode was allowed to move freely for 1–2 h before being immobilized by 1 ml of 10 mM sodium azide applied at the bacterial spots. In most assays, worms quickly entered one bacterial lawn and remained there for the duration of the assay. A two-choice behavior assay was also conducted as indicated in C. elegans, 200 μl of L. zeae LB1 culture was spread on a plate, and the nematode was kept on the plate for 2 h at 25°C prior to the two-choice behavior assay. Each treatment was repeated three times. Choice index of A against B = (number of worms in the lawn of bacterium A – number of worms in the lawn of bacterium B)/total worm number. If choice index = −1.0 represents complete preference for bacterium B, then +1.0 represents complete preference for bacterium A, 0.0 represents an equal distribution  control, (2) DT104 infection only, and (3) L. zeae LB1 pretreatment. In the control, the nematode was treated with E. coli OP50 only throughout the entire assay. In the DT104 infection only, the L4 stage nematode was incubated with E. coli OP50 for 18 h followed by incubation with 200 μl of DT104 for up to 7 days in the absence of E. coli OP50. In the L. zeae LB1 pretreatment, the nematode was incubated with 200 μl of L. zeae LB1 for 18 h followed by incubation with 200 μl of DT104 for up to 7 days in the absence of E. coli OP50. The incubation temperature was 25°C. Each assay was started by transferring L4 stage worms (25 worms per replicate and three replicates per treatment) onto the agar plates seeded with either E. coli OP50 or L. zeae LB1, which was designated as day 0. After 18 h of incubation, worms on each plate within each treatment (either DT104 infection only or L. zeae LB1 pretreatment) were transferred to a fresh NGM plate daily that had been seeded with DT104 and was subsequently incubated at 25°C. The control group was processed in parallel, in which worms were transferred to a fresh NGM plate daily that had been seeded with E. coli OP50. The survival of nematode was examined at 24-h intervals for up to 7 days. To determine the survival of C. elegans, the number of live worms was recorded daily and calculated as follows: survival rate (%) =  × 100. A worm was considered to be dead when it failed to respond to touch with a platinum loop; each treatment was repeated three times.The life-span assays of Fresh worms were washed three times with RNase-free water and lysed using the proteinase K-based method  with iTaq™ Universal SYBR Green Supermix  under the conditions as follows: 95°C for 3 min followed by 40 cycles of denaturing at 95°C for 30 s, annealing at 56°C for 1 min, and extension at 72°C for 30 s. The PCR primers are listed in Gene expression levels were determined by quantitative PCR (QPCR) analysis, following reverse transcription using qScript™ cDNA SuperMix  according to manufacturer's protocol; 1–2 μl of cDNA template was used for a QPCR assay. Two housekeeping genes, gapdh and −ΔΔCt method  control group within the same treatment. The WT groups had the 2−ΔΔCt value of 1.The fold changes of target genes were determined using the 2cat-2 were cultured on NGM agar containing dopamine and seeded with OP50 until they reached L4 stage. In the life-span assay, the entire procedure of the mutant, including L. zeae LB1 pretreatment, DT104 infection, and subsequent observation, was conducted in the presence of dopamine. The WT was treated in parallel without exposure to dopamine to serve as a reference.Previous studies have shown that exogenous dopamine added to experimental plates or buffers can mimic the effects of a dopaminergic signaling, although a relatively high concentration is required to elicit a response in the assay due to the low permeability of cuticle to dopamine . Survival curves of Caenorhabditis elegans to different bacterial odor was firstly investigated in a free-choice assay. C. elegans was significantly attracted to Lactobacillus zeae LB1 (P ≤ 0.05), but not to other bacteria. Approximately 92% worms moved to L. zeae LB1, 5% to DT104, and 3% to OP50 in the assay.The preference of L. zeae LB1 can alter the preference of C. elegans toward DT104, binary choice assays without  or dopamine (cat-2) was also investigated in the two-choice assay. Both mutants exhibited similar choice behavior to the WT to the tested bacteria  were examined in the same assay . For example, the survival rate of infected WT was 43.33 ± 6.67% at the seventh day, while that of uninfected WT was 91.00 ± 1.51%. Mutants tph-1 and cat-2 both succumbed faster than the WT after DT104 infection (P ≤ 0.05). At the seventh day, tph-1 and cat-2 had a survival rate of 32.22 ± 5.03%  to DT104 infection were also investigated. Synchronized L4 stage WT worms were treated with L. zeae LB1 for 18 h followed by Salmonella Typhimurium DT104 infection for up to 7 days. The results showed that the survival rate of the WT pretreated with L. zeae LB1 was higher than that of the same worms infected with DT104 only, indicating that L. zeae LB1 pretreatment for 18 h significantly increased the resistance of the WT to S. Typhimurium infection (P ≤ 0.05) as reported previously  in the life-span assay of C. elegans. As shown in cat-2 defective in dopamine production succumbed faster than the WT to S. Typhimurium infection (P ≤ 0.05), which was in agreement with the observation shown in cat-2 to the infection (P ≤ 0.05), in which the survival rate was 34.00 ± 1.34% at the seventh day compared with 28.00 ± 0.68% in the group without dopamine supplementation. When the concentration of dopamine reached 0.5 mM and above (up to 1.5 mM), the resistance of cat-2 was further enhanced (P ≤ 0.05) with the level similar to the WT infected with DT104 only.To determine the involvement of dopamine in the host defense to L. zeae LB1 are given in L. zeae LB1 offered no protection to mutant cat-2 when there was no supplementation of dopamine. However, the protection of L. zeae LB1 was generated by dopamine in a dose-dependent manner (0–1.5 mM). In particular, the survival rate (~70%) of mutant cat-2 exposed to 0.75 and 1.5 mM of dopamine was comparable with that of the WT without exposure to dopamine when both were subjected to the pretreatment of L. zeae LB1 and DT104 infection. These results indicate that exogenous dopamine at 0.75 mM and above can fully restore the protection of L. zeae LB1 to the nematode mutant against S. Typhimurium DT104 infection.The effects of supplementation of dopamine on restoring the protection of C. elegans as well as the pathogenicity of DT104 in the life-span assay, the assays were performed with the WT nematode that had been either infected or not with DT104 in the absence and presence of dopamine (0.75 and 1.5 mM). At both the dopamine concentrations, C. elegans had a similar survival rate to the worms without dopamine treatment regardless if the nematode had been infected with DT104 or not. Similarly, the same level of growth of DT104 in a liquid medium was also observed regardless if dopamine (0.75 and 1.5 mM) was supplemented or not. These results indicate that exogenous dopamine at the tested concentrations had no effects on the viability of both DT 104 and C. elegans as well as the pathogenicity of DT104.To determine whether dopamine supplementation affected the viability of DT104 and cat-2 in response to the supplementation of dopamine in the life-span assay, the gene expression of major components in the p38-MAPK  and IGF-1/DAF-16 (age-1 and daf-16) pathways, previously identified antimicrobial peptides , and other reported defense molecules  was examined with the method described previously  and p38-MAPK (pmk-1 and sek-1) pathways or for defense functions (dbl-1 and spp-1) were all down-regulated in mutant cat-2 compared with the WT (P ≤ 0.05), and the supplementation of dopamine (1.5 mM) restored their expression back to the level in the WT . One exception was the up-regulation of skn-1 expression (involved in defense function) in the mutant, which substantially exceeded the expression level in the WT (P ≤ 0.05). However, the supplementation of dopamine (1.5 mM) down-regulated its expression back to the level observed in the WT.To determine the cell signaling of mutant cat-2 worms supplemented without/with 1.5 mM of dopamine were incubated with OP50 for 18 h followed by DT104 infection for 48 h, and the gene expression was then examined. Similarly, age-1, daf-16, pmk-1, sek-1, dbl-1, and spp-1 all expressed at low levels in S. Typhimurium infected mutant cat-2 (P ≤ 0.05), and the supplementation of dopamine (1.5 mM) also restored their expression back to the level in the WT (skn-1 was up-regulated in the mutant in the absence of dopamine but down-regulated after dopamine supplement (P ≤ 0.05).In parallel B, L4-stage n the WT . Again, cat-2 worms supplemented without/with 1.5 mM of dopamine were treated with L. zeae LB1 for 18 h followed by DT104 infection for 48 h, and the gene expression was then examined. The six genes  demonstrated a similar pattern of gene expression profile (either down-regulation or up-regulation) in the mutant that had been subjected to both S. Typhimurium infection and L. zeae LB1 pretreatment before and after the supplementation of dopamine when compared with the WT  and innate immune signaling pathways (pmk-1 and sek-1) was significantly down-regulated in the mutant defective in cat-2, and supplementation of dopamine to mutant cat-2 restored the expression of these genes to the level in the WT. These results appear to support the notion that dopaminergic signaling has a role in regulating the IGF-1/DAF-16 and innate immune signaling pathways in C. elegans.It has been shown that neurotransmitters can regulate immune responses. A regulatory axis from the gut microbes to neurotransmitter and then to autoimmune system was proposed in both rodents and humans Tognini, . Xue et C. elegans to various pathogens or toxins was based on the expression level of genes with a defense function, which was mediated by the IGF/DAF-16 or p38-MAP kinase signaling pathways  suggest a role of the IGF-1/DAF-16 and innate immune signaling pathways mediated by dopamine in the nematode resistance, which is consistent with the report that C. elegans may use a neuronal circuit to regulate protective functions via longevity and innate immune signaling pathways to combat bacterial infection when encountered with bacterial pathogens. Similarly, Anyanful et al. (C. elegans. In addition, Kamaladevi and Balamurugan (Lactobacillus casei triggered a TLR-mediated p38 MAPK pathway to increase host resistance and protect nematodes against pathogen infection. In view of these descriptions, our data support the same notion; i.e., the nervous and immune systems can communicate and influence each other in order for the nematode to rapidly and effectively protect themselves from bacterial infection. Given that the signaling pathways are highly conserved from C. elegans to humans (Weidhaas et al., The degree of host susceptibility of l et al.  found thamurugan  reportedC. elegans to S. Typhimurium infection. The protection offered by L. zeae LB1 was not dependent on modifying olfactory preference of the nematode but was mediated by dopamine. In addition, both p38-MAPK and IGF-1/DAF-16 signaling pathways appeared to be involved in the regulation of the protection.In summary, the present study has demonstrated that both serotonin and dopamine play a positive role in the host defense of The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.XL, LJ, HY, and JG designed the experiments. XL, LJ, and LL performed the research. XL, LJ, LL, HY, and JG analyzed data. SN and MX contributed to discussion and resource provision. XL, LJ, and JG wrote the manuscript. JG and MX conceived the research. All the authors approved the final version of manuscript.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.


Increasingly, there has been recognition that siloed approaches focusing mainly on human health are ineffective for global antimicrobial resistance (AMR) containment efforts. The inherent complexities of AMR containment warrant a coordinated multisectoral approach. However, how to institutionalize a country’s multisectoral coordination across sectors and between departments used to working in silos is an ongoing challenge. This paper describes the technical approach used by a donor-funded program to strengthen multisectoral coordination on AMR in 11 countries as part of their efforts to advance the objectives of the Global Health Security Agenda and discusses some of the challenges and lessons learned.The program conducted a rapid situational analysis of the Global Health Security Agenda and AMR landscape in each country and worked with the governments to identify the gaps, priorities, and potential activities in multisectoral coordination on AMR. Using the World Health Organization (WHO) Joint External Evaluation tool and the WHO Benchmarks for International Health Regulations (2005) Capacities as principal guidance, we worked with countries to achieve key milestones in enhancing effective multisectoral coordination on AMR.The program’s interventions led to the achievement of key benchmarks recommended actions, including the finalization of national action plans on AMR and tools to guide their implementation; strengthening the leadership, governance, and oversight capabilities of multisectoral governance structures; establishing and improving the functions of technical working groups on infection prevention and control and antimicrobial stewardship; and coordinating AMR activities within and across sectors.A lot of learning still needs to be done to identify best practices for building mutual trust and adequately balancing the priorities of individual ministries with cross-cutting issues. Nevertheless, this paper provides some practical ideas for countries and implementing partners seeking to improve multisectoral coordination on AMR. It also demonstrates that the WHO benchmark actions, although not intended as an exhaustive list of recommendations, provide adequate guidance for increasing countries’ capacity for effective multisectoral coordination on AMR in a standardized manner. Antimicrobial resistance (AMR) is internationally recognized as a global threat to humans, animals, the environment, and consequently the global economy and health security. It is estimated that 700,000 people die annually from AMR, a rate that is projected to increase to 10 million by 2050 if adequate and decisive action is not taken , 4. AMR Previous AMR containment efforts were often siloed, focusing mainly on the human health sector. However, that approach is no longer considered adequate due to potential implications of widespread antimicrobial use, not just in human health, but also in animal health; the agricultural, husbandry, and fishery sectors; as well as environmental contamination through antimicrobial residual discharge. It is now recognized that food from animals can transmit resistant infections to humans . Hence, Several global activities have occurred over the past two decades that have helped advance MSC. In May 2005, the World Health Assembly adopted the International Health Regulations (IHR) (2005), which aim to prevent, protect against, control, and respond to public health threats and their underlying causes. IHR (2005) has 19 technical areas, of which AMR is one. The World Health Assembly also adopted the global action plan on AMR based on the One Health approach in 2015 . Member The Global Health Security Agenda (GHSA), established in 2014, brings together stakeholders, including countries, international organizations, and the private sector, to accelerate progress on attaining security from global health threats posed by infectious diseases. GHSA is an expanding partnership, supporting 69 countries in improving their capacity in 19 technical areas, including AMR, and uses the JEE to measure countries’ progress in these areas . The GHSSince its inception in September 2018, the US Agency for International Development (USAID) Medicines, Technologies, and Pharmaceutical Services (MTaPS) program has been a key mechanism for USAID’s GHSA support to partner countries in the areas of antimicrobial stewardship (AMS), infection prevention and control (IPC), and MSC on AMR (MSC-AMR). One of MTaPS’ aims is to help its GHSA-supported countries progress toward the next level of JEE capacity for effective MSC-AMR , WHO, FAO, schools of medicine and pharmacy, hospitals, professional associations , and the animal sector. The visits enabled us to build relationships with country stakeholders and increase attention to AMR, including from a GHSA perspective. Based on the rapid situational analysis, we worked in concert with governments to identify potential activities in MSC-AMR and develop work plans.The desk reviews and scoping visits helped identify strengths, gaps, and priorities for MSC-AMR, and informed the program’s interventions, which included specific benchmark actions and other activities that contributed to the achievement of the benchmarks.Although the version of the JEE tool used for the baseline evaluations did not include an indicator for MSC-AMR, the reports outlined some of the challenges and recommended actions pertinent to MSC. The primary issues identified in the JEE baseline reports included: the need to finalize, validate, or disseminate NAPs-AMR, establish multisectoral technical groups to implement AMR plans, and strengthen the capacity of facilities and entities that would play roles in One Health policies Table . AnotherBy the time of the scoping visits, some of the issues identified in the JEE baseline had already been addressed. For example, the JEE reports indicated that Bangladesh, Burkina Faso, Cameroon, Côte d’Ivoire, DRC, Mali, Senegal, and Tanzania needed to develop or finalize their NAPs-AMR. However, Bangladesh, Cameroon, Senegal, and Tanzania had already finalized theirs at the time of the scoping visits while the other countries had drafts at various stages of development.The situational analyses revealed that all countries had an established One Health platform and high-level political commitment to AMR containment. However, some countries had issues with inadequate institutionalization of the platform. Generally, the animal sector was less active on AMR relative to the human sector, and the environmental sector was the least active. All countries were struggling to varying degrees with finalizing or operationalizing their NAPs-AMR and MSC-AMR bodies. The coordination and relationships between the MSC-AMR body and the One Health body were generally unclear and weak. Additionally, there was often no clear synergy observed between the mainstream AMR work and the GHSA’s support in this area. The MSC-AMR bodies were primarily established at the central level, but Bangladesh and Kenya had at least articulated aims to expand multisectoral coordination mechanisms to subnational levels in their national action plan or strategy on AMR. Weaknesses in MSC-AMR were often due to inadequate political support, authority to act, administrative and financial support, AMR data availability or use, and practical know-how on the process and parameters of how such bodies should operate. The MSC-AMR bodies in some cases were established without clear supporting policies regarding funding and human resources. The gaps in capacity and function of the MSC-AMR bodies were constraining the countries’ progress in implementing the NAP-AMR objectives—including those on IPC and AMS—and hence overall progress on AMR containment.Given the findings from the scoping visits, MTaPS prioritized strengthening the function and technical capacity of multisectoral governance structures as a critical intervention to operationalize NAPs-AMR and strengthen capacity for AMR containment in all its 11 GHSA/AMR-supported countries. We chose the interventions based on the specific guidance on MSC-AMR (indicator P.3.1) now included in the revised 2018 edition of the JEE tool and the corresponding WHO benchmarks recommended actions (hereafter benchmark actions)  Table . We workIn some countries, MTaPS supported the development of implementation or operational plans and monitoring and evaluation (M&E) frameworks to guide NAP-AMR implementation. Both steps are recommended benchmark actions to move to demonstrated capacity (level 4). The human, animal, agriculture, and environment sectors and partner organizations in Cameroon collaborated to draft an operational plan for their NAP-AMR. Bangladesh and Kenya developed a multisectoral M&E framework for their NAP-AMR.National stakeholders in Ethiopia and Senegal drafted and submitted funding concept notes to the Tripartite AMR Multi-Partner Trust Fund (MPTF) with support from MTaPS. MPTF is a newly established vehicle to fund partner countries’ intersectoral collaboration to implement the NAP-AMR. This effort contributes to a level 4 benchmark action—identifying and mapping sustained funding for planned activities in the AMR national action plan Table .DRC and Ethiopia conducted the Tripartite AMR Country Self-Assessment Survey (TrACSS) for 2019–2020 in collaboration with MTaPS. TrACSS is a component of the global framework to monitor NAP-AMR implementation status, and countries report the self-assessment results to the tripartite group for global summary. Conducting this annual self-assessment helps illustrate the country’s progress in building an effective and sustainable collaborative multisectoral work and response to AMR.Implementation has also included work on communication to increase AMR awareness in Bangladesh, Kenya, Tanzania, and Uganda. Acting on Tanzania’s NAP-AMR, MTaPS led the development of a multisectoral communication strategy to increase awareness and understanding of AMR across all sectors. The country’s Multisectoral Coordination Committee on AMR approved the strategy in February 2020. The government and AMR stakeholders began using the standardized messages from the AMR communication strategy during the World Antimicrobial Awareness Week 2020. Furthermore, the document is used by AMR stakeholders to promote behavior change to improve the appropriate use of antimicrobials among health care providers and the wider community.Uganda’s NAP-AMR also has the promotion of AMR awareness as one of its objectives. MTaPS helped develop and validate guidelines for infection prevention and appropriate use of antimicrobials in all the leading farming systems in Uganda—cattle, fish, goats and sheep, pigs, and poultry. The Ministry of Agriculture, Animal Industry, and Fisheries leadership plan to use these guidelines widely. We also collaborated with stakeholders in Bangladesh, Burkina Faso, Côte d’Ivoire, Ethiopia, Kenya, Tanzania, and Uganda to organize AMR awareness events during the World Antimicrobial Awareness Week in November 2019 and/or 2020. For example, in Tanzania in 2019 the program brought together 700 participants for an AMR symposium organized by Tanzania Pharmaceutical Students’ Association. In Bangladesh, the program facilitated two round table discussions on antimicrobial use around World Antimicrobial Awareness Week 2020 with participants from the national government, FAO, WHO, Fleming Fund, pharmaceutical industry and trade associations, professional associations, the media, and other implementing partners.While the name of the MSC-AMR body varies across countries, in all cases it is a mandated governance mechanism that represents the highest level of multisectoral coordination on AMR in the country. The MSC-AMR body typically has TWGs, which are responsible for the technical implementation of the various strategic objectives in the country’s NAP-AMR, such as IPC, AMS, and surveillance. Although all the countries had an MSC-AMR body, their functionality was often weak. We therefore focused on working with these bodies to develop or revise their TORs (including the formation of TWGs) to strengthen governance mechanisms, and organize effective coordination through regular meetings, both of which are recommended level 3 benchmark actions for improving the function of MSC-AMR bodies Table . AdditioTo help bolster AMR governance in Ethiopia, we supported the Pharmaceutical and Medical Equipment Directorate to conduct an assessment to understand the level of engagement of government stakeholders in AMR containment. The results revealed a weak coordination mechanism for AMR stakeholders; a lack of a monitoring and evaluation framework to measure progress; no central reporting channel on AMR-related activities; and the absence of functional TWGs in line with the One Health approach to combat AMR. As a result, Ethiopia finalized the design of a three-tiered national AMR governance and coordination structure, comprising a National Inter-Ministerial Committee at the top, the National AMR Advisory Committee (NAMRAC), and six multisectoral TWGs. NAMRAC, whose membership includes the human health, animal health, food, and environmental sectors, revised its TOR to align with the WHO’s sample TOR for an MSC-AMR body . The revInstituting routine, organized meetings for the MSC-AMR bodies has led to their demonstrated leadership of some AMR-related activities. For example, the lack of regular communication among GCMN-RAM members in Mali had been a major hindrance to coordination. With our technical and financial support, GCMN-RAM conducted its first two meetings with participants from the health and social affairs, agriculture, livestock and fisheries, and environment ministries, and international organizations, including USAID, FAO, OIE, and WHO. GCMN-RAM now has a validated TOR and led the revision of the country’s NAP-AMR. MTaPS has since worked with the GCMN-RAM and the Hygiene Sub-Directorate of the Direction Générale de la Santé to revise IPC guidelines for the human sector and draft associated training materials. A subsequent validation workshop in January 2020 had the participation of IPC stakeholders at the central and regional levels, including all the heads of hygiene and sanitation divisions in Mali’s 10 regions. The final guidelines are now available and include training curriculum, participants’ manual, and training modules on IPC topics.MTaPS facilitated multisectoral meetings of the MSC-AMR bodies in Bangladesh, Côte d’Ivoire, DRC, Ethiopia, Kenya, and Senegal to review the implementation status of their NAPs-AMR. For example, the Pharmaceuticals Unit and the Pharmaceutical and Medical Equipment Directorate of the Ministry of Health in Ethiopia conducted a workshop with regional health bureaus to review implementation status. As a result, each region agreed to assign an AMR focal person to coordinate the region’s actions against AMR, develop a regional action plan, and strengthen or reestablish regional AMR advisory committees. We also supported the AMR secretariat in adapting the national strategy on AMR to a regional action plan in the Somali Regional State. This process included federal and regional offices of human health, animal health, academia, and the regional laboratory, and demonstrated how the larger national strategy can align with regional realities to prevent and contain AMR.In Uganda, the One Health TWG provides leadership for the National Antimicrobial Resistance Sub-Committee (NAMRsC), the MSC-AMR body. The chair of the One Health TWG rotates every 3 months between the MOH, Ministry of Agriculture, Animal Industry and Fisheries, and the Ministry of Water and Environment. This strengthens leadership, incentivizes ownership and collaboration among the ministries, and helps motivate the NAMRsC members appointed by their respective ministries. The NAMRsC appointed one person each from the IPC technical working committee, AMS technical working committee, and the Ministry of Water and Environment to support the 2019 national IPC survey conducted by the MOH, in collaboration with MTaPS, WHO, and other local implementing partners. The team has since supported surveys in AMS areas, including surveillance of the consumption of antibiotics at various health facilities. These survey findings have been shared in the quarterly NAMRsC meetings and used by the MOH to identify priority activities to improve the national IPC program. NAMRsC also collaborates with other programs, such as the Fleming Fund, to implement AMR-related activities throughout the country. These examples demonstrate how such MSC-AMR bodies have moved beyond meetings to specific actions to support AMR containment.MTaPS worked with the MSC-AMR bodies in nine countries to establish or revitalize multisectoral or multidisciplinary IPC or AMS TWGs Table . In someIn Cameroon, Côte d’Ivoire, DRC, Tanzania, and Uganda, where some TWGs did not exist, we worked with the MSC-AMR body to help establish them Table . For exaIn countries where the TWGs already existed, our efforts focused on developing or revising TORs, helping to coordinate regular meetings, and developing policies and guidelines for IPC and AMS Table . In TanzThe functionality of existing multisectoral coordination bodies is perhaps most evident and timely in responding to the COVID-19 pandemic. IPC TWGs or some of their members contributed to national pandemic response in Bangladesh, Cameroon, Côte d’Ivoire, Ethiopia, Kenya, Mali, Senegal, Tanzania, and Uganda Table . In thosTable In Tanzania, MTaPS worked to advance MSC by organizing multiple workshops that brought together stakeholders from the FAO, Ministry of Livestock and Fisheries, and the Tanzania Mainland Ministry of Health. At one of these workshops in September 2019, participants, including WHO, CDC, Sokoine University of Agriculture, the environmental sector, and the National Medicines and Therapeutic Committee, carried out a final review of the draft AMS policy guidelines, which were then finalized by the Multisectoral Coordination Committee in November 2019 and approved in December 2020. Similarly, through our efforts in Uganda, major national and subnational IPC stakeholders, representing MOH, Makerere University, WHO, the One Health platform, Infectious Diseases Institute, and other partners, convened and drafted TORs for the national IPC technical working committee. In Burkina Faso, MTaPS collaborated with the Directorate General of Environmental Protection to provide sensitization to a high-level audience on the importance of antimicrobial stewardship and strengthening of the legal framework on AMR during an environmental conventions workshop organized for parliamentarians. As part of its civil society organization engagement strategy in Ethiopia, MTaPS collaborated with the MOH to provide a 3-day training on AMR to 29 volunteers from the Ethiopian Youth and Women Federations on AMR, 21 (72%) of whom were women. Those female volunteers subsequently conducted educational sessions on the rational use of antimicrobials for 520 members of the Addis Ababa Women Federation.In its 2019 final report to the Secretary-General of the United Nations, the Interagency Coordination Group (IACG) on Antimicrobial Resistance identified four categories of countries with respect to progress made on NAPs-AMR: (1) no plan or strategy on AMR; (2) preparing a plan or in the process of approving a plan; 3) have a plan but experiencing difficulty in implementation; 4) have a plan or strategy that is being implemented  have a p. The cou have a pAs found in the scoping visits, some aspects of an enabling environment, such as high-level political will, already existed in the 11 countries. However, both the level of political will and awareness of the AMR issue varied among stakeholders and across sectors. By bringing stakeholders together through the strengthening of MSC-AMR, MTaPS has helped increase both political will and awareness across sectors. In Côte d’Ivoire, for instance, the advocacy document developed by the AMR TWG to accompany the NAP-AMR will be used to advocate for high-level commitment and increase awareness across different ministries. Similarly, communication efforts to boost AMR awareness in Tanzania and Uganda will contribute to a more enabling environment.Many of the countries MTaPS supports lack adequate funding sources and monitoring processes for NAP-AMR implementation, which, in some cases, was due to insufficient details regarding operational plans, costing, and monitoring and evaluation. This issue was compounded by poor data availability and monitoring, and weak diagnostic and regulatory capacities throughout the health system. Adequate monitoring and feedback mechanisms are critical for tracking progress and aligning targets among collaborators . AMR conOngoing interventions in the 11 countries have directly or indirectly helped to address some of those identified challenges by focusing efforts on strengthening governance mechanisms for MSC-AMR. Operationalizing NAPs-AMR through costed and prioritized operational plans with monitoring and evaluation frameworks and the necessary technical support has been a major MTaPS priority. The focus on developing and revising TORs for these bodies helps to ensure clarity about the roles and responsibilities of members and stipulates the structures and processes for accountability and oversight, which are all critical for these mechanisms’ function. WHO provides a sample TOR, which has been a useful resource to help countries strengthen the function of their MSC bodies . We haveMTaPS support for both the national MSC-AMR body and its associated IPC/AMS TWGs allowed the program to leverage its activities between the different levels of the system  and enhance vertical coordination in countries such as Côte d’Ivoire, Kenya, and Tanzania. Further, TWGs serving specific technical areas can reach downstream to targeted groups that can directly and effectively support technical interventions, as seen in Côte d’Ivoire and Tanzania, where the TWGs supervised and supported facilities to advance IPC and AMS actions.The emergence of COVID-19 has created an unprecedented global challenge and since March 2020, MSC-related program activities in most of the countries have slowed due to countries shifting their priorities toward addressing the pandemic. It is important to note, however, that some of the IPC TWGs created or strengthened through our interventions have quickly used their enhanced capacity to support their countries’ pandemic response through, for example, assisting with or advising on the development of training curriculum and the development of national guidelines and action plans.Whereas the animal sector is becoming more engaged in the AMR response in the 11 countries, environmental sector engagement continues to be weak. Coordination across diverse sectors that normally work in silos is not always easy. The principle of multisectoral collaboration is now widely acknowledged and accepted, however, the complexity of coordination within and across sectors continues to be a challenge . At the Despite the progress made in improving AMR awareness, critical gaps remain that undermine MSC-AMR efforts and the successful implementation of NAP-AMR. Behavior change is a strategic objective of the global action plan on AMR and countries’ NAP-AMR, but many countries lack the support needed to achieve this objective. This gap needs more attention, including practical skills-building in applying behavioral interventions. Also, wider base of support for behavioral and other interventions can be garnered by strategically framing AMR as a value-add to existing initiatives rather than as a stand-alone competing priority . BecauseThrough the WHO’s IHR and GHSA’s ongoing efforts, AMR is increasingly being addressed as a national, regional, and global health security threat. Although the WHO benchmark actions are not intended as an exhaustive list of recommendations, our multi-country experience shows that the tool has filled a key gap in implementation guidance. The benchmark actions have served as an effective and standardized yardstick for measuring countries’ capacity for effective MSC-AMR, allowing countries to move progressively towards the next JEE capacity level.The existence of a NAP-AMR and MSC-AMR body is necessary but insufficient to address AMR containment . NAPs-AMCoordinating across and within sectors and creating ownership and collaboration through mutual trust require time and dedicated resources . This prThe program has also found that working with stakeholders, including those across and within different levels of ministries, academia, and professional associations, to create strategies, plans, guidelines, and curricula, is an efficient catalyst for sharing knowledge and information to reach targeted players in AMR containment . HoweverThe paper reports work in progress, and the MSC-AMR bodies have not yet had time to demonstrate a substantial number of outcome-oriented actions. As such, progress, challenges, and lessons learned will continue to evolve during the program. Furthermore, the paper’s scope is restricted to the work of the MTaPS program with the work of other partners included to a limited extent. It therefore does not comprehensively address the MSC-AMR landscape related to support from other partners. In addition, the GHSA mandate of the MTaPS program is limited to MSC-AMR, and IPC and AMS in human health, and the scope of work did not allow this paper to cover the area of AMR surveillance nor adequately incorporate the perspectives of the larger national health security mechanisms.MSC is a core policy of the One Health approach aimed at global AMR containment. Given the multiple drivers of AMR, including those rooted in the health, food, animal, and environmental sectors, containing AMR calls for a coordinated response from stakeholders across multiple sectors. How to institutionalize MSC across sectors and between departments that normally work in silos is an ongoing challenge. Developing a NAP-AMR is a substantial step and signifies good political commitment toward AMR containment. However, actually operationalizing it to achieve AMR containment and contribute to GHSA, IHR, universal health coverage, and SDGs will require an adequately resourced and sustained multisectoral approach that is backed by enabling policies, guidelines, and operating procedures. As our findings in this paper show, the JEE tool and WHO benchmarks were highly useful guides to achieving key milestones in AMR containment—finalization of NAPs-AMR and tools to guide their implementation; strengthening the leadership, governance, and oversight capabilities of multisectoral governance structures, including establishment or revitalization of IPC and AMS TWGs; and coordinating AMR activities within and across sectors. This paper therefore provides some practical ideas for countries and their international partners and demonstrates the feasibility of implementing the WHO benchmarks recommended actions to strengthen multisectoral coordination on AMR.


A large body of work has linked dopaminergic signaling to learning andreward processing. It stresses the role of dopamine in rewardprediction error signaling, a key neural signal that allows us tolearn from past experiences, and that facilitates optimal choicebehavior. Latterly, it has become clear that dopamine does not merelycode prediction error size but also signals the difference between theexpected value of rewards, and the value of rewards actually received,which is obtained through the integration of reward attributes such asthe type, amount, probability and delay. More recent work has positeda role of dopamine in learning beyond rewards. These theories suggestthat dopamine codes absolute or unsigned prediction errors, playing akey role in how the brain models associative regularities within itsenvironment, while incorporating critical information about thereliability of those regularities. Work is emerging supporting thisperspective and, it has inspired theoretical models of how certainforms of mental pathology may emerge in relation to dopamine function.Such pathology is frequently related to disturbed inferences leadingto altered internal models of the environment. Thus, it is critical tounderstand the role of dopamine in error-related learning andinference. Dopamine is a critical modulatory neurotransmitter. Acting within distinctpathways, it is involved in a wide range of functions, including the controlof movement, motivation, reward processing, and learning. Its perturbationhas been linked to profound neurodegenerative and psychiatric impairments. In the unsigned PEs),they indicate whether outcomes were better or worse than expected,resulting in positively and negatively signed PEs . Theseegned PEs. Signed gned PEs. While tgned PEs, its rolNeuroscience research broadly defines rewards as any positive, orpleasurable, outcomes, that we are motivated to obtain and thatwe will work for . TodeteDopamine is synthesized by dopamine neurons and thence transportedvia axonal projections widely throughout the brain. Althoughdopamine has multiple functions, the brain contains relativelyfew dopamine neurons; ~400,000 in the human brain which accountsfor ~1% of the total neuronal population . The majIn animals, the phasic (fast spiking) and tonic (slower responses)of VTA/SN dopamine neurons can be measured directly using singlecell electrophysiology . These pIn humans, brain responses in the VTA/SN are mainly investigatedusing functional neuroimaging techniques  such as functionalMRI (fMRI) and position emission tomography PET; . fMRI meThe idea of RPEs has long been central to ideas of classical andinstrumental conditioning and to reinforcement learning (RL)generally. RL has its roots in the seminal work of Ivan Pavlovon classical (Pavlovian) conditioning in dogs , as wellWhereas Pavlov focused on situations in which the outcome (food)followed the conditioned stimulus (bell) irrespective of anybehavioral reaction, Edward Thorndike  andBurrWith regard to the involvement of RPE in RL, one key observationwas that, if the PE is absent, learning does not occur even whena cue is strongly associated with an outcome. This is famouslydemonstrated in Kamin’s blocking effect , in whicReinforcement Leaning (RL).RL. Formal RL models foster a more mechanisticunderstanding of the different computations that a neuralsystem must solve to translate to changes in behavior. Afirst formal  model of RL was developed byRobert Rescorla and Allan Wagner, termed theRescorla-Wagner (RW) model (W) model , which sHere, predictions of reward value :Another strategy for weighting earlier outcomes, and hencePEs, more than later ones, is to reduce the learning rateas trials progress. Decreasing your rate of learning astime progress is sensible as one’s predictions become morereliable (and hence new outcomes less informative) as timeprogresses. where the recursive process is initialized with the initiallearning rate Extending RL Models to Decision Making. Theabove models speak directly to the relationship betweencues and (predicted) outcomes. Models based on similarprinciples have extended the ideas to instrumentalconditioning, where the context-dependent value ofdifferent action options must be tracked and used tooptimize choice behavior. One simple but powerful instanceof this is the Q-learning model  and choosingB(Qb), on thebasis of individual sequences of choices and outcomes.This value, termed a Q value, isessentially the expected reward obtained by taking thatparticular action. After every trial n> 0 the value of the chosen stimulus is updatedaccording to the following rule:ng model . This isQ value:and the PE is calculated using the following formula toindicate the difference between the predicted value of thechosen option and the maximum discounted futureQ values, the associatedprobability of selecting each action is then estimated byimplementing a softmax rule , the likelihood that a reward will occur in this state,and how a decision may change the state . Optimal decision making therefore requires individualsto predict future states, which can be learned from state PEs RL models relate RPEs and learning tothe value we assign to a particular reward . The queThese insights have led researchers to investigate rewards in termsof subjective rather than objective values . SubjectIn 1997, a clear neuronal substrate of RPEs was observed . SchultzIn humans, the hypothesized role of dopamine in RPE signaling hasbeen strongly supported by studies using neuroimaging andpharmacological dopaminergic manipulations. Usinghigh-resolution fMRI, A large number of studies have confirmed the role of the VTA/SN andthe striatum in the signaling of RPEs across both direct andindirect rewards . See Fighidden, and thatlonger cue-reward delays increased the belief that reward wasomitted and that a state transition had occurred.Optogenetically identified dopamine neurons showed the highestresponses to the latest rewards, suggesting that animals hadinferred a state transition (to the ISI state) and no longerexpected reward. The authors also found that a revised TD modelthat included a belief state, which tracks the probability ofbeing in each state produced PE signals that resembled dopamineRPEs. In line with this, others found that administration ofL-DOPA to healthy individuals increased model-based overmodel-free choice  “state” that ananimal is in . Each tre choice . Howevere choice .It is important to note here that the encoding of RPEs is notlimited to the VTA/SN as other regions show responses dependingon the nature for reward . SpecifiIn addition to its role in RPE coding, there is incomplete evidence thatdopamine encodes salience, that is, the extent that a stimulus isparticularly noticeable . FocusinThe debate on the role of dopamine in attributing salience focuses inpart on whether salience attribution is limited to events that arelikely associated with rewards. One line of evidence shows thatphysically salient sensory stimuli, such as tones and lights, evokevery rapid (50-110 ms), phasic excitations in dopamine neurons . This raAs introduced above, a particular type of salient stimuli that recruitdopaminergic responses relate to novelty . For insunsigned) PE signal indicates thedegree to which an outcome is unexpected, independent of its sign, andthereby controls the rate of learning , insula and dorsal striatum .NeurophIt should be noted though that, in this study, all PEs occurred in areward context and it is not clear whether brain responses that do notdistinguish negative and positive PEs might be different fromresponses to PEs that are unrelated to rewarding outcomes. It isconceivable that the potential sensitivity of dopamine to unsigned PEsis still geared toward rewards and would not occur for unrewardedstimuli .A further interesting observation comes from investigations of brainresponses to rewards that are matched in (expected) value but differin reward type/identity . Such identity or sensory PEs engendersurprise and can as such be considered salient. Using sensorypreconditioning  andoptogenetics in rodents, recent work showed that the acquisition ofinformation about transitions between non-rewarding events is alsodriven by PEs and that, dopamine transients were sufficient to supportthis type of learning .These fMotivational salience refers to the quality that drives approach behaviorfor rewarding outcomes and avoidance behavior for aversive outcomesonce the physical salience, surprise, and RPEs associated with astimulus or option have been processed . Such saWhile neurons in the non-human primate SN increase their firing rate atvery short latencies to unexpected stimuli, independent of whetherthey were rewards or punishment , some haOverall, there is relative consensus that mesolimbic dopamine plays arole in the attribution of physical and surprise salience . It is, There are several accounts integrating the proposed roles of dopamine inreward prediction (error coding) and salience. For instance, In addition, formal learning models such as hybrid RW-PH RL models (Box1) include a role for surprise as well as the RPE. Here, RPEs drivethe trial-wise extent of learning, whereas surprise drives changes inthe learning rate across time. Importantly, such hybrid models betterpredict individuals’ learning behavior than these models alone .Furthermore, investigations in learning models that include choicebehavior (Box 1), indicate that increases in dopamine activationresulting from increases in positive PEs increases the likelihood ofchoosing an action that leads to reward .ConsistDrawing on recent advances in artificial intelligence, In addition, some authors have hypothesized that dopamine neurons serve afar more general function in signaling the expectation of (any)information  or signauniquely codes RPEs, or whether this is oneof the (many) functions of dopamine. In light of the work discussedabove, the most pressing enquiry is to establish whether dopamineneurons might compute any type of PE, independent of its domain, andhow dopamine neurons interact with other brain systems to supportother types of learning. The first question could be addressed bytesting PEs in different domains, using tasks in which value is heldconstant or absent. In addition, it would be important to test forseveral types of PEs at the same time to scrutinize accounts of“multidimensional” PE signaling  across sensory and cognitive domains.Furthermore, in these models behavior is optimal, not when reward ismaximized, but rather when surprise (or the PE) is minimized.Moreover, they state that dopamine does not code an RPE, but rathercodes the precision or reliability of the PE. These models alsodirectly link perception and beliefs with both engaged in making senseof inputs by inferring their causes, an idea that goes back to VonHelmholtz . As PEs In the predictive processing framework, there is a hierarchy wherelower-level PEs signal violations of a sensory nature, while higherorder PEs signal violations of beliefs about the probabilisticstructure of the environment and its volatility  and hence more informative. Lowerprecision can result from unclear predictions , from noisy perceptual stimuli , high variability in the association between differentoutcomes, and changes in previously learnt associations orenvironmental volatility . WhereasAlthough many studies have demonstrated support for approximate Bayesianinference, there is little direct experimental evidence tosubstantiate predictive coding, processing, and active inferenceframeworks. Some preliminary work using fMRI and PET found that beliefupdating activated the human VTA/SN and striatum independent ofsurprise or RPEs, and that these brain responses correlated withmidbrain dopamine D2/D3 receptor availability and striatal dopaminerelease capacity . This hoAlthough these studies provide initial support for a role of dopamine incoding PEs beyond reward, and playing a critical role in the buildingand updating of internal models of the world, it is important toestablish the role of dopamine in this process as the SN/VTA containdopaminergic and non-dopaminergic neurons . FurtherIt is well known that dopamine interacts with other neurotransmitters,and that there is evidence of other neurotransmitters coding PEs. As acomprehensive overview of this topic is beyond the scope of thisreview, we illustrate this with the use of a few, select,examples.Although much of the evidence is indirect, glutamate has frequently beenassociated with PE coding neurons inhibit dopamine neurons when reward is expected, withcontributes to the calculation of RPEs , afindiA deeper understanding of the precise role of dopamine in PE coding and relatedfunctions is not merely of theoretical interest as dopamine dysfunction hasbeen implicated in a range of diseases, including Parkinson’s disease,Huntington’s disease, substance use disorders, depression, anxiety disorder,and attention hyperactivity deficit disorder. There is particularly powerfulevidence linking altered dopamine function to psychosis in the context ofillnesses such as schizophrenia . AlthougPsychosis has consistently been linked to increased presynaptic dopamine in thestriatum , with thPsychosis has been associated with dysfunctions in a number of thedopamine-mediated processes described above  and negative symptoms of psychosis  relates to a system’s computational goal while the other,predictive coding, is an “algorithmic motif” . AprediA wealth of studies has confirmed the role of dopamine in RPE coding, using alarge range of different techniques and validation across different species,including rodents, monkeys, and non-human primates. It is, however, likelythat dopamine has an additional role in signaling the amount of surprisedassociated with a rewarding outcome or stimulus, which can well beintegrated with the RPE framework. Finally, novel models suggest an entirelydifferent role for dopamine in PE coding across the whole brain, which mightbe exceptionally important for understanding clinical conditions associatedwith altered dopamine processing such as psychosis. It will be crucial toinvestigate these novel accounts in future studies using experimentaldesigns and data, and to further the work on the link between these modelsand clinical conditions.


Much of the research in biology aims to understand the origin of diversity. Naturally, ecological diversity was the first object of study, but we now have the necessary tools to probe diversity at molecular scales. The inherent differences in how we study diversity at different scales caused the disciplines of biology to be organized around these levels, from molecular biology to ecology. Here, we illustrate that there are key properties of each scale that emerge from the interactions of simpler components and that these properties are often shared across different levels of organization. This means that ideas from one level of organization can be an inspiration for novel hypotheses to study phenomena at another level. We illustrate this concept with examples of events at the molecular level that have analogs at the organismal or ecological level and vice versa. Through these examples, we illustrate that biological processes at different organization levels are governed by general rules. The study of the same phenomena at different scales could enrich our work through a multidisciplinary approach, which should be a staple in the training of future scientists. Louis Bernatchez gave Christian his first glimpse at how the sequence of genes can tell the history of a population or a species in a class on Molecular Ecology at Université Laval. After his undergraduate studies, Christian was interested in studying human population genetics and Louis gave him the contact information of some laboratories where he could join a graduate program to pursue this. However, all the laboratories he contacted advised him to first do a MSc with Louis before starting his graduate studies; advice that in hindsight was indeed very good. Between 1998 and 2000, Christian did his master's research in Louis’ laboratory, investigating the diversity of genes in the Major Histocompatibility Complex. This was Louis’ first project looking at nuclear coding gene sequences, most other projects were using “neutral” markers  to make inferences about population structure. Christian's main interest in biology was the study of evolution, and his work under the guidance of Louis’ was enlightening as this is where he discovered that evolution could be studied directly, not only inferred. After completing his MSc program and spending a few months as a research professional in Louis’ laboratory, Christian went on to enter a PhD program at Harvard University . Now as an independent PI of just over ten years, the early guidance of Louis is still an inspiration in how to create and sustain a healthy and productive research team, without sacrificing a well‐rounded and happy personal life.1We work on several aspects of evolution using a range of methods. Among other things, we are interested in how genes are born  to pursue exciting work in multidisciplinary and integrative research.2Biologists often study the collective behavior of organisms, cells, or molecules. These collective behaviors are fascinating because they display properties that are not observable from the study of a single organism, cell, or molecule. Such emerging properties refer to new functionalities that arise from interactions between the elements of a system that would not be found in any of the parts acting in isolation Johnson, . PropertAt larger molecular scales, macromolecules also show complex behaviors from relatively simple pairwise interactions. One of the simplest forms is a chain of nucleotides, which on their own have no enzymatic activity but when organized into polymers with specific sequences can acquire enzymatic properties and become ribozymes  are generated by monitoring the interactions (represented by “edges” of the network) between species (represented by “nodes” of the network)  is unevenly distributed among the nodes Figure ,c. A fewThe degree distribution can be fitted to a power law equation Figure ,c. NetwoIn order to understand the dynamics of ecological systems, network architecture provides an efficient medium because one can estimate how the removal of a node will likely affect other elements of the network  to the topological properties of their underlying networks, which themselves depend on rather simple pairwise interactions among their components. System properties therefore transcend levels of organization.4Biological networks are not static throughout evolution. They can change by adding new elements or removing existing ones. In the case of ecological networks, new species can be added by speciation events. One species can diverge into several new ones Kocher, , and difGene duplication produces an identical copy of a preexisting gene, usually through errors in DNA replication, cell division, unequal crossing over during recombination, or retrotransposition events . This phenomenon has been observed at the binding sites of interacting proteins  and evade recognition. This is famously exemplified by the common cuckoo, Candida albicans  within genomes. If we consider the completion of a single cell cycle through a mitotic division, each canonical gene on each chromosome of a given genome is replicated exactly once, and both resulting cells inherit one copy of this gene. In contrast, TEs can replicate more than once within a single cell cycle, with copies of themselves invading new loci on chromosomes (McClintock, Arabidopsis, as regions near genes are deprived in methylated TEs (Ahmed, Sarazin, Bowler, Colot, & Quesneville, TEs will often encode genes that are necessary but not sufficient for their own replication. For example, retrotransposons encode genes that are essential for their own reverse transcription and integration into the host genome (Wicker et al., In summary, arms races and conflicts are common themes that emerge from the comparison of selfish components within genomes and ecosystems. Thus, it can be expected that these conflicts lead to the emergence of complex systems that cannot be explained by adaptive evolution of host features alone, but rather by compensatory evolution in the face of cheaters.8Molecular biology and ecology have analogous properties that can be exploited in teaching and research. We expanded on these ideas by discussing how molecular phenomena closely resemble what is seen at the organismal level. These parallels call for deeper integration of the fields since models from one field can inspire models for analogous processes in the other. For example, networks can be used to represent interactions between molecules and between species equally well; new functions and species can emerge from modification of the existing ones; and arms races have been described at the species and molecular levels. While we focused on these examples that are close to our fields of research, there are potentially many more.Having concepts carry over between fields allows models to be transferable. As described above, networks have been used at both the molecular and ecological levels. The well‐established framework of networks has contributed to the advancement of both fields to solve analogous problems, such as the identification of genes involved in diseases (Yu, Kim, Xiao, & Hwang, Traditionally, molecular biology and ecology are taught separately as if they were somehow disconnected. Considering the similarities between molecular biology and ecology, a case can be made for a more integrative approach in teaching. This kind of organization could potentially lead to advancement of both fields by bringing students to think about the overarching properties of biological systems. We believe that students’ curricula and activities could be modified to facilitate better communication between these fields and to focus on commonalities among systems rather than on the differences. From a pedagogical point of view, narratives from one level can be borrowed to help teach key concepts at other levels, depending on the training of the people involved. As a result, future professionals and researchers would be able to come up with original ideas to study and understand nature better as a whole.


Antimicrobial resistance (AMR) is a major health concern worldwide. A better understanding of the underlying molecular mechanisms is needed. Advances in whole genome sequencing and other high-throughput unbiased instrumental technologies to study the molecular pathogenicity of infectious diseases enable the accumulation of large amounts of data that are amenable to bioinformatic analysis and the discovery of new signatures of AMR. In this work, we review representative methods published in the past five years to define major approaches developed to-date in the understanding of AMR mechanisms. Advantages and limitations for applications of these methods in clinical laboratory testing and basic research are discussed. Antimicrobial resistance (AMR) contributes to antibiotic (AB) treatment failure and increasing rates of mortality in various infectious diseases. Misuse of specific AB and overuse of broad spectrum AB are attributed to the emergence of AMR, which in some strains results in multidrug resistance (MDR). As MDR organisms become more common in clinical settings, fast and accurate assessment of antibiotic susceptibility is needed to start effective treatment as soon as possible . HoweverDecades of research into various molecular mechanisms of AMR have revealed scores of antibiotic resistance genes (ARG), or bacterial gene variants associated with phenotypical resistance to AB. An example is the NCBI Bacterial Antimicrobial Resistance Reference Gene Database (NCBI Accession ID: PRJNA313047). Resistance can develop in many ways, depending on the target. Staphylococcus aureus to determine whether it is methicillin-resistant S. aureus (MRSA) and therefore requires modification of a typical antibiotic treatment approach. Unfortunately, many types of resistance are more complex as there is often incomplete penetrance of the ARG, and thus simple association with phenotypic resistance, such as mecA, is not possible, especially when trying to generalize ARG across multiple species or while evaluating multiple AB at once [The mechanism of action of many AMR genes or cellular pathways are already known. In some cases where the genotype–phenotype relationship is straightforward, gene-based prediction has found its way into clinical practice in the form of rapid molecular tests. An example is the detection of the mecA gene in  at once .With the advent of whole genome sequencing (WGS) permitting quick access to de novo sequenced genomes of pathogens and the collection of sufficiently large datasets of clinical isolates, it is now plausible to employ advanced bioinformatics approaches  to gain new insights in the more complex molecular mechanisms of AMR. These approaches can evaluate many samples at once by exploring different types of data  and reveal new insights previously not attainable.In the past few years, the field of biomedical AMR prediction has evolved rapidly. In this review, we summarize the current state of bioinformatics methods for the discovery of AMR molecular mechanisms and discuss advantages and limitations of machine leaning (ML) models in the prediction of AMR and their use in clinical settings.The first approach to predicting the AMR is to analyze WGS  data by identifying the presence of known ARG or gene variants. Some genes are endogenous to a given species/strain, while others reside on mobile genetic elements (plasmids) that can be shared between species. The corresponding binary (presence or absence) or real number (abundance) vectors that represent such fixed sets of genes and their mutations can be subsequently used for training ML models and predicting newly sequenced samples.S. aureus [E. coli, C. jejuni, and S. enterica. PhyResSE [M. tuberculosis (strain H37Rv) in order to identify what lineage a given isolate represents from a pre-compiled catalog of 92 lineages with known resistance phenotype. The method eliminates the need for genome assembly step but requires a number of additional steps for assuring the quality of called variants, including FastQC [S. aureus and M. tuberculosis susceptible and resistant to multiple AB [M. tuberculosis complex isolates, then using only 9 ARG along with mutations to predict susceptibility to 4 AB [TypeWriter uses BLASTn to match assembled genomic contigs to 24 ARG and 120 mutations associated with resistance in . aureus . The ass. aureus . The maiPhyResSE  applies PhyResSE , a fasteg FastQC , Qualimag FastQC , and Geng FastQC ,20. PhyRtiple AB . Then, rM. tuberculosis, as this is very hard to grow), and it is not clear yet if this type of model would work equally well on other species with potentially more complex AMR mechanisms.Collectively, these methods operate with a predefined panel of ARG and associated mutations. They can yield accurate results with high confidence applicable in clinical settings. The sequencing of a bacterial genome has become fast (about 24 h and decreasing) and does not require several days of additional growth in vitro, as is required for traditional laboratory AMR testing. This could decrease the time to start effective AB therapy, thereby improving patient outcomes. Of note, most of these methods have been developed for only one specific pathogen  and to metagenomics samples  could be low.E. coli evolution in the lab under pressure of 11 AB with different concentrations to obtain strains resistant to these drugs with various degrees, measured in terms of minimum inhibitory concentrations (MIC) [acrB, ompF, cyoC, pps, tsx, oppA, folA, and pntB) whose expression levels allowed for a linear regression model achieving correlation with experimentally determined MIC with R2 ranging from 0.54 to 0.75 per drug. Darnell and colleagues studied transcriptional response of E. faecalis (strain JH2-2) to teixobactin [E. faecalis to other cell wall targeting antimicrobials revealed the shared upregulated CroRS regulon of 219 genes. CroRS is the cell wall stress response two-component system (TCS). The corresponding deletion mutant (ΔcroRS) significantly increased susceptibility of the organism to teixobactin.The second approach to the AMR analysis and prediction is to study changes in gene expression of the isolate upon drug treatment. Suzuki and colleagues induced ns (MIC) . Subsequxobactin . Genome-E. coli, and identification of informative differentially expressed transcripts may further be delayed by the need of functional annotation to understand their role in AMR. The analysis of complex isolates like microbiome samples presents even bigger challenges, as these metatranscriptomics data need deconvolution before they can be useful in any research or prediction.Overall, this approach represents great promise in studying AMR molecular mechanisms. We envision that besides known dynamic mechanisms, such as overexpression of genes targeted by AB and xenobiotic efflux transporters, new studies may reveal regulatory circuits responding to various toxic stimuli  and other compensatory mechanisms. However, given the complexity of the experiments, and the long time required to generate and analyze the data, this approach is unlikely to be employed in clinical settings soon, especially given the current modest accuracy of prediction. Moreover, not all clinically important pathogens (and their strains) are as well annotated as E. coli, both commensal and outbreak-related, with respect to their genomic content and gene expression profiles [E. coli outbreaks that were subsequently characterized with Gene Ontology (GO) and mapped to genomic functional modules defined in the KEGG database [M. tuberculosis and S. aureus, but they went further than the former study and extracted any 31-mers of genomic sequences (including from noncoding regions) that were uniquely associated with given pairs of drugs and AB susceptibility levels [k-mers  to be used in linear regression models for each tested AB with performance on par with the state of the art methods, such as Mykrobe. After assembly of these k-mers into unitigs and aligning them to the annotated genome, all k-mers appeared to belong to 10 genes or RNA: the embB gene for ethambutol, fabG1—ethionamide, katG and fabG1—isoniazid, rss and eis—kanamycin, gyrA—ofloxacin, rpoB—rifampicin, and rss and rpsL—streptomycin. Kavvas and colleagues [M. tuberculosis based on 1595 sequenced strains and employed additional information from the PATRIC database [2, and ANOVA F-test) and a machine learning algorithm , they were able to identify 24 new genetic signatures of AMR and reveal 97 epistatic interactions associated with 10 classes of resistance in M. tuberculosis. Subsequent mapping to available 3D structures of select proteins associated with AMR allowed the authors to pin point the clusters of mutations in these proteins in response to AB. Such additional insight may help one to better understand the AMR causality of alleles in future studies. The latest and most comprehensive work within this approach was published by Drouin and colleagues and covers 12 bacterial species and 56 drugs [k-mers associated with susceptible or resistant strains, they applied rule-based ML algorithms—Classification and Regression Trees (CART) and Set Covering Machines (SCM). These rule-based models provide clues to the importance of specific k-mers in decision making, which may facilitate the discovery of new mechanisms of AMR in different organisms.The third approach to elucidating the AMR mechanisms is gene agnostic and based on global genomic comparison of multiple strains with various susceptibility to different drugs. PanPhlAn compared 110 reference and 12 metagenomically detected strains of profiles . The comdatabase . Mahe an56 drugs . In addiThe pan-genome approach, while requiring a prior large investment in genomic sequencing and genome wide comparison, also holds great promise for clinical application. The major advantage of this approach is exploring whole genomes instead of just known AMR-related regions, potentially identifying new mechanisms or regulatory elements . The challenge of these methods for machine learning is that the input space is very large  and detection of novel regions needs rigorous evaluation  in order to validate its importance. This is because association between certain genomic regions in samples with similar AMR can be purely statistical rather than causal, a concept known as overfitting of ML models. Furthermore, these methods often require large collections of strains to obtain informative insights in AMR, something that would be a challenge for under-studied pathogens.E. coli with 3 AB and analyzed the changes in the metabolite profiles [E. coli lineages under pressure of various combinations of 3 AB, but they also altered carbon source in the culture media to force either respiratory or fermentative metabolism of glucose [acrB. It was observed that E. coli employs multiple mechanisms to compensate for the pressure from different antibiotics, either via mutations or expression of efflux pumps; it also depends on the carbon source and therefore metabolic state the organism is in. This observation further supports the notion that Gram-negative bacteria are more complex to study and predict in terms of genotype–phenotype in the context of AMR.The last approach, orthogonal to those described above, takes advantage of metabolic profiling. Yang and colleagues treated profiles . By comb glucose . In addiE. coli.Collectively, this approach gives a new perspective on the understanding of AB action and response of bacteria to drugs. While it is far from being easily translated to clinical practice, this approach lays the foundation to improve drug treatment regimens and optimize combined therapies. Extension of this approach to other pathogenic organisms may present challenges, since not all species are as well studied in terms of metabolic pathways as the model organism Bioinformatics approaches to the AMR research can be broadly categorized as those that focus on fast and reliable predictions of AMR to be applied in clinical settings, and those that explore the underlying molecular mechanisms of AMR. The first category primarily stems from prior knowledge of AMR molecular mechanisms, and may better generalize patterns of genotype–phenotype relationships. With the advent of WGS technologies, approaches in the first category tend to utilize sequencing data in order to identify the presence of known signatures of AMR, such as resistance genes or specific alleles known to elicit resistance. Approaches from the second category employ more difficult-to-generate data or complex datasets, such as pan-genomes, gene expression profiles, metabolomics, or biological pathways. The latter approaches are more geared towards revealing novel resistance genes, epistatic interactions related to AMR, underlying regulatory mechanisms, or new drug targets.Each considered approach possesses certain limitations, discussed in the corresponding sections, and they should be considered when building and evaluating new prediction models. Nevertheless, the combination of modern molecular methods and powerful ML algorithms holds great promise for the understanding of AMR at the molecular level and for improved clinically relevant predictions leading to a more personalized AB use and more favorable clinical outcomes.


The strength of goal-oriented behaviors is regulated by midbrain dopamine neurons. Dysfunctions of dopaminergic circuits are observed in drug addiction and obsessive-compulsive disorder. Compulsive behavior is a feature that both disorders share, which is associated to a heightened dopamine neurotransmission. The activity of midbrain dopamine neurons is principally regulated by the homeostatic action of dopamine through D2 receptors (D2R) that decrease the firing of neurons as well as dopamine synthesis and release. Dopamine transmission is also regulated by heterologous neurotransmitter systems such as the kappa opioid system, among others. Much of our current knowledge of the kappa opioid system and its influence on dopamine transmission comes from preclinical animal models of brain diseases. In 1988, using cerebral microdialysis, it was shown that the acute activation of the Kappa Opioid Receptors (KOR) decreases synaptic levels of dopamine in the striatum. This inhibitory effect of KOR opposes to the facilitating influence of drugs of abuse on dopamine release, leading to the proposition of the use of KOR agonists as pharmacological therapy for compulsive drug intake. Surprisingly, 30 years later, KOR antagonists are instead proposed to treat drug addiction. What may have happened during these years that generated this drastic change of paradigm? The collected evidence suggested that the effect of KOR on synaptic dopamine levels is complex, depending on the frequency of KOR activation and timing with other incoming stimuli to dopamine neurons, as well as sex and species differences. Conversely to its acute effect, chronic KOR activation seems to facilitate dopamine neurotransmission and dopamine-mediated behaviors. The opposing actions exerted by acute versus chronic KOR activation have been associated with an initial aversive and a delayed rewarding effect, during the exposure to drugs of abuse. Compulsive behaviors induced by repeated activation of D2R are also potentiated by the sustained co-activation of KOR, which correlates with decreased synaptic levels of dopamine and sensitized D2R. Thus, the time-dependent activation of KOR impacts directly on dopamine levels affecting the tuning of motivated behaviors. This review analyzes the contribution of the kappa opioid system to the dopaminergic correlates of compulsive behaviors. Compulsion is the impossibility of self-stopping to execute a habitual action with known outcome, despite adverse consequences . Compulssubstantia nigra (SN) and ventral tegmental area (VTA), which target the dorsal and ventral tiers of the striatum, respectively. Dopamine neurons that project to the ventral striatum or nucleus accumbens (NAc) have been traditionally related to goal-oriented behaviors, whereas dopamine neurons that project to the dorsal striatum have been associated with habits acquisition (One possible mechanism leading to compulsive behavior is framed within the incentive-sensitization theory of addiction which is that an amplified motivation (“wanting”) for the drug develops during addiction without developing an amplified pleasurable (“liking”) effect . Endurinuisition .Sensitization of the reward/motivation circuit is observed in rodents as the gradual increase in locomotor activity induced by repeated administration of a potentially addictive drug fixed dose . LocomotThe kappa opioid system is one of the most preponderant systems controlling dopamine transmission in the reward/motivation circuit. Evidence shows that kappa-opioid transmission opposes to the effects of dopamine; the acute activation of kappa opioid receptors (KORs) counteracts the locomotor activity induced by psychostimulants . ConversThe thorough analysis carried out recently shows that the effect of the kappa-opioid system on dopaminergic transmission is complex: it depends on the dopamine pathway involved , and on KORs are Gi/o protein-coupled receptors highly expressed in the midbrain dopamine system . These rSeveral experimental approaches show that the activation of KORs inhibits dopamine release. The acute activation of KORs by a systemic injection or the local infusion of agonists decreases the extracellular levels of dopamine in the NAc  and dors, in vitro and in vivo functional data suggests that KORs modify dopamine extracellular levels by modulating the activity of DAT. For instance, the activation of KORs in EM4 cells that co-express KORs and DAT, lead to an increased uptake of dopamine measured by voltammetry  it decreases locomotor activity, while at higher doses (>0.5 mg/kg), it increments. . These eAt the beginning of the 90's, Szechtman and Eilam reported that along with locomotor sensitization, rats developed a stereotyped behavior, which is reinforced with each administration of quinpirole . Today, in vivo consists of tonic and burst firing  and high (postsynaptic) doses of quinpirole. U69593 changed the hypolocomotor effect of a presynaptic dose of quinpirole to hyperlocomotion and enhanced the hyperlocomotor effect of a postsynaptic dose of quinpirole . Co-actiThe crosstalk between D2Rs and KORs is complex and it seems to depend on whether the activation of both receptors is coincident or temporally separated. Anatomical data indicate that the crosstalk between D2Rs and KORs can occur presynaptically in axons and soma of dopamine neurons, as well as postsynaptically in MSNs of the striatum. Although it does not rule out a role for KORs located on axons of other neurochemical systems, the anatomical data strongly points to a direct role of KORs regulating D2Rs. Either acute or repeated, the activation of KORs decreases the inhibitory D2Rs function on dopamine neurons. Electrophysiology studies showed that the acute activation of KOR in dopamine neurons of the VTA and SN inhibits D2R-mediated inhibitory postsynaptic current, an effect mediated by pre and postsynaptic mechanisms as KOR decreases dopamine release and dynorphin blocks the inhibitory effect of bath applied dopamine . NeurochA recent study shows that KOR activation in the VTA mediates compulsive behavior measured as behavioral inhibition and marble burying , reinforRemarkably, KOR was found in MSNs of the NAc , thus inClinical studies have shown sex differences in compulsive behavior including compulsive drug seeking. An earlier onset of OCD symptoms is observed in men compared with women , with woin vitro experiments showed that estradiol plus progesterone restore amphetamine-induced dopamine release from striatal tissue obtained of ovariectomized female rats (Lately, pre-clinical evidence has strongly highlighted the neurobiological bases underpinning the sex differences in drug abuse observed in clinical studies . Early oale rats . More reale rats . These sale rats .The regulation of KOR on dopamine extracellular levels also shows sex differences . Using iAlthough a facilitation in psychostimulant induced dopamine release is observed in female compared to male rats, sex differences in the dopamine mechanisms underlying amphetamine locomotor sensitization have not been fully elucidated . The repHow do KORs modulate dopamine signaling to elaborate motivated behaviors and when does it result in a sensitized compulsive behavior? Anatomical data shows that KORs are exquisitely positioned to control the synaptic activity of midbrain dopamine neurons. Functional data indicate that KORs control DAT and D2R functioning as well as dopamine neurons firing rate. Initial evidence showing that the acute activation of KORs decreases dopamine release induced by drugs of abuse has been complemented with data indicating that the repeated activation of KOR facilitates dopamine release and compulsive drug-seeking. Dopamine signaling balance direct and indirect output pathways from striatal areas (AE, MA, and JF contributed to the conception of the manuscript. AE and JF wrote the first draft of the manuscript with input from MA. MA and JC contributed to the critical review and editing of the manuscript. All the authors approved it for publication.The work of the authors cited in this review has been supported by FONDECYT grant numbers: 1110352 and 1150200 to MA; 1141088 to JF; DIPOG grant 391340281 to JF; FONDECYT Postdoctoral fellow 3170497 to JC and 3190843 to AE.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.The handling editor is currently organizing a Research Topic with one of the authors JF, and confirms the absence of any other collaboration.