Mariko Matsui
email: mmatsui@pasteur.nc

Julie Cagliero

Sharon Y A M Villanueva

Leptospirosis Pathophysiology: Into the Storm of Cytokines

Keywords: Leptospira, leptospirosis, inflammatory response, cytokine storm, immunoparalysis, susceptible/resistant hosts

Leptospirosis is a neglected tropical zoonosis caused by pathogenic spirochetes of the genus Leptospira. Infected reservoir animals, typically mice and rats, are asymptomatic, carry the pathogen in their renal tubules, and shed pathogenic spirochetes in their urine, contaminating the environment. Humans are accidental hosts of pathogenic Leptospira. Most human infections are mild or asymptomatic. However, 10% of human leptospirosis cases develop into severe forms, including high leptospiremia, multi-organ injuries, and a dramatically increased mortality rate, which can relate to a sepsis-like phenotype. During infection, the triggering of the inflammatory response, especially through the production of cytokines, is essential for the early elimination of pathogens. However, uncontrolled cytokine production can result in a cytokine storm process, followed by a state of immunoparalysis, which can lead to sepsis and associated organ failures. In this review, the involvement of cytokine storm and subsequent immunoparalysis in the development of severe leptospirosis in susceptible hosts will be discussed. The potential contribution of major pro-inflammatory cytokines in the development of tissue lesions and systemic inflammatory response, as well as the role of anti-inflammatory cytokines in contributing to the onset of a deleterious immunosuppressive cascade will also be examined. Data from studies comparing susceptible and resistant mouse models will be included. Lastly, a concise discussion on the use of cytokines for therapeutic purposes or as biomarkers of leptospirosis severity will be provided.

INTRODUCTION

Leptospirosis is a re-emerging neglected zoonosis, caused by pathogenic spirochete bacteria from the genus Leptospira and estimated to infect more than a million people with approximately 60,000 deaths annually (Costa et al., 2015a,b;[START_REF] Picardeau | Leptospirosis: updating the global picture of an emerging neglected disease[END_REF]. Number of fatal cases is comparable to or even higher than some other important neglected tropical diseases such as severe dengue or visceral leishmaniasis [START_REF] Picardeau | Leptospirosis: updating the global picture of an emerging neglected disease[END_REF]. Leptospirosis occurs after direct or indirect contact with bacteria shed in the urine of reservoir animals, mostly rodents, in which infection is asymptomatic and results in chronic renal carriage [START_REF] Adler | Leptospira and leptospirosis[END_REF]. Clinical manifestations in infected humans are extremely variable, including flu-like symptoms, and spontaneously resolve in 90% of cases [START_REF] Haake | Leptospirosis in humans[END_REF][START_REF] Gomes-Solecki | Animal models of leptospirosis: of Mice and Hamsters[END_REF]. However, 10% of patients develop severe forms of the disease and are designated as susceptible hosts in this review. Severe human leptospirosis is characterized by multi-organ failures and is associated with a dramatic increase in the mortality rate [START_REF] Adler | Leptospira and leptospirosis[END_REF][START_REF] Haake | Leptospirosis in humans[END_REF].

Hepatic dysfunctions associated with renal failure and hemorrhages constitute Weil's syndrome, a severe form of leptospirosis [START_REF] Haake | Leptospirosis in humans[END_REF]. Acute kidney injury (AKI) is commonly reported as an early manifestation of acute leptospirosis and could possibly evolve to chronic kidney disease (CKD) [START_REF] Correa-Rotter | CKD of unknown origin in Central America: the case for a Mesoamerican nephropathy[END_REF][START_REF] Herath | Long term outcome of acute kidney injury due to leptospirosis? A longitudinal study in Sri Lanka[END_REF]. Severe pulmonary hemorrhagic syndrome (SPHS) with acute respiratory distress syndrome (ARDS) can also occur and can be confused with viral pneumonitis [START_REF] Trevejo | Epidemic leptospirosis associated with pulmonary hemorrhage-Nicaragua 1995[END_REF][START_REF] Haake | Leptospirosis in humans[END_REF].

Although it is still unclear why leptospirosis patients present with various clinical manifestations, both innate and adaptive immune responses to Leptospira infection influence the outcome of the disease. Induction of an inflammatory response due to an infection with a pathogen can initiate destructive immune mechanisms leading to host tissue damages, sepsis and death. Interestingly, the cytokine storm process was suggested to have a role in the development of severe leptospirosis, especially in humans [START_REF] Reis | Cytokine response signatures in disease progression and development of severe clinical outcomes for leptospirosis[END_REF][START_REF] Haake | Leptospirosis in humans[END_REF]. In this review, we summarized evidences supporting this hypothesis, mainly based on results from studies on hosts susceptible and resistant to lethal infection.

INFLAMMATORY RESPONSE TO LEPTOSPIRA INFECTION

During an infection, contact with pathogens activates the innate immune system by generating an inflammatory response. Microbial Pathogen-Associated Molecular Patterns (PAMPs) will be recognized by the Pattern Recognition Receptors (PRRs) expressed at the surface of innate immune cells, mainly the Tolllike receptors (TLRs) and nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) [START_REF] Akira | Pathogen recognition and innate immunity[END_REF]. The PAMPs/PRR association triggers an inflammatory cascade by activating multiple intracellular signaling pathways, including the NF-κB and activator protein 1 (AP-1) transcription factors [START_REF] Schroder | The inflammasomes[END_REF], which in turn regulate the expression of cytokines, Prostaglandins (PGs), and Nitric Oxide (NO) [START_REF] Tisoncik | Into the eye of the cytokine storm[END_REF][START_REF] Turner | Cytokines and chemokines: at the crossroads of cell signalling and inflammatory disease[END_REF]. PGs and NO are pro-inflammatory molecules that increase arterial dilation and vascular permeability, both being key events required for the influx of immune cells [START_REF] Ricciotti | Prostaglandins and inflammation[END_REF][START_REF] Wink | Nitric oxide and redox mechanisms in the immune response[END_REF]. Pro-inflammatory cytokines include interleukins (IL)-1β, IL-6, IL-12, interferons (IFNs) and tumor necrosis factors (TNFs), as well as chemokines, which act as chemoattractants to recruit leucocytes to the site of tissue damage and/or infection [START_REF] Tisoncik | Into the eye of the cytokine storm[END_REF][START_REF] Turner | Cytokines and chemokines: at the crossroads of cell signalling and inflammatory disease[END_REF]. Interestingly, AP-1 and NF-κB also modulate the pro-inflammatory response through the induction of immunomodulatory cytokines as IL-4, IL-10, IL-13 or Transforming Growth Factor-β (TGF-β) acting in concert with cytokines inhibitors to offset the massive induction of proinflammatory mediators [START_REF] Dinarello | Historical review of cytokines[END_REF][START_REF] Turner | Cytokines and chemokines: at the crossroads of cell signalling and inflammatory disease[END_REF].

Data show that leptospiral PAMPs stimulate innate immunity through several PRRs to produce cytokines and activate the inflammatory cascade, as was recently reviewed by C. Werts [START_REF] Werts | Interaction of leptospira with the innate immune system[END_REF]. Mechanisms underlying the specific leptospiral PAMPs/PRR-triggered inflammation have not yet been fully elucidated. Interestingly, in contrast to other bacterial LPS (e.g., from E. coli) that classically activates TLR4 signaling pathway, leptospiral LPS is not recognized by TLR4, but by TLR2 in human cells, while both TLR2 and TLR4 are activated in mice [START_REF] Nahori | Differential TLR recognition of leptospiral lipid A and lipopolysaccharide in murine and human cells[END_REF]. Moreover, TLR4-deficient mice develop clinical signs of severe leptospirosis [START_REF] Gomes-Solecki | Animal models of leptospirosis: of Mice and Hamsters[END_REF], which show that murine TLR4 protect mice from developing leptospirosis. This species specificity in leptospiral PAMPs sensing also suggest that hosts could trigger different inflammatory responses according to their susceptibility to leptospirosis.

CYTOKINE STORM IN SEVERE LEPTOSPIROSIS

Inflammatory cytokines and cytokine regulators interact in a complex network finely controlled to clear the pathogens without excessive inflammation-induced organ damage. Indeed, severe infectious diseases are often associated with a prolonged increase in pro-inflammatory IL-1β, TNF-α, IL-6 expression, or "cytokine storm, " causing persistent inflammation and followed by a massive and systemic production of anti-inflammatory cytokines, causing a state of "immunoparalysis" [START_REF] Tisoncik | Into the eye of the cytokine storm[END_REF][START_REF] Zhao | The growing spectrum of anti-inflammatory interleukins and their potential roles in the development of sepsis[END_REF]. Consequently, tissue edema impairs local organ perfusion, which can result in loss of organ function; furthermore, prolonged endothelial permeabilization can lead to pathogen invasion into the bloodstream and result in a sepsislike syndrome [START_REF] Cohen | The immunopathogenesis of sepsis[END_REF][START_REF] Tisoncik | Into the eye of the cytokine storm[END_REF]. In fact sepsis is now defined as a life-threatening organ dysfunction caused by a dysregulated host response to an infection [START_REF] Singer | The third international consensus definitions for sepsis and septic shock (Sepsis-3)[END_REF] and is referred to as a "cytokine storm-induced syndrome" [START_REF] Chousterman | Cytokine storm and sepsis disease pathogenesis[END_REF].

Clinical signs of severe leptospirosis in susceptible hosts include increased leptospiremia and multi-organ failure, specifically affecting kidneys, liver and lungs [START_REF] Levett | Leptospirosis[END_REF][START_REF] Haake | Leptospirosis in humans[END_REF][START_REF] Yilmaz | Characteristics of leptospirosis with systemic inflammatory response syndrome: a multicenter study[END_REF]. Interestingly, these clinical features meet the criterions for a sepsis diagnosis, which suggest that development of severe leptospirosis could be associated with a dysregulated inflammation. Interestingly, data obtained from clinical studies support this hypothesis. The very first quantifications of cytokines in human leptospirosis showed significant increase in TNF-α level from patient sera [START_REF] Duell | Recent insights into microbial triggers of interleukin-10 production in the host and the impact on infectious disease pathogenesis[END_REF][START_REF] Tajiki | Association of plasma levels of Tumour Necrosis Factor α with severity of disease and mortality among patients with leptospirosis[END_REF][START_REF] Tajiki | The ratio of plasma levels Of Il-10/Tnf-alpha and its relationship to disease severity and survival in patients with leptospirosis[END_REF]. Further investigations reported higher production of cytokines in severe compared to mild disease [START_REF] Reis | Cytokine response signatures in disease progression and development of severe clinical outcomes for leptospirosis[END_REF][START_REF] Mikulski | Severity markers in severe leptospirosis: a cohort study[END_REF][START_REF] Chirathaworn | Cytokine levels as biomarkers for leptospirosis patients[END_REF]. Serum levels of proinflammatory IL-6, chemokine IL-8 and anti-inflammatory IL-10 were significantly higher among patients that developed SPHS compared to non-SPHS leptospirosis patients [START_REF] Reis | Cytokine response signatures in disease progression and development of severe clinical outcomes for leptospirosis[END_REF]. In addition, concentrations of these cytokines were elevated in sera from patients with organ dysfunction compared to mild cases without organ involvement [START_REF] Chirathaworn | Cytokine levels as biomarkers for leptospirosis patients[END_REF]. Experimental infection also showed evidence of differential pattern of cytokine expression depending on resistance or susceptibility of animal models (Figure 1). Strictly regulated induction of pro-inflammatory cytokines IL-1β, IL-6, TNF-α and chemokines CXCL10/IP-10 and CCL3/MIP-1α in resistant mice contrasted with delayed and massive overexpression in susceptible hamsters developing severe tissue lesions [START_REF] Matsui | Gene expression profiles of immune mediators and histopathological findings in animal models of leptospirosis: comparison between susceptible hamsters and resistant mice[END_REF]. Overexpression of anti-inflammatory IL-10 was faster and at higher levels in resistant mice than in hamsters [START_REF] Matsui | High level of IL-10 expression in the blood of animal models possibly relates to resistance against leptospirosis[END_REF]. Moreover, expression of TNF-α, IL-1α, and IL-10 were significantly higher in lethally infected hamsters compared to survivors (Vernel-Pauillac and Goarant, 2010). Based on these, dramatic imbalance in the cytokine production upon Leptospira infection might play a considerable role in the development of severe leptospirosis.

ROLE OF CYTOKINES IN THE PATHOPHYSIOLOGY OF SEVERE LEPTOSPIROSIS Pro-inflammatory Cytokines

Although TNF-α was the first cytokine to be associated with leptospirosis severity [START_REF] Duell | Recent insights into microbial triggers of interleukin-10 production in the host and the impact on infectious disease pathogenesis[END_REF][START_REF] Tajiki | Association of plasma levels of Tumour Necrosis Factor α with severity of disease and mortality among patients with leptospirosis[END_REF], its precise role in the disease pathophysiology is still under debate. Macrophage apoptosis induced by L. interrogans in vitro is triggered via caspase-8 and caspase-3-dependant pathways [START_REF] Jin | Leptospira interrogans induces apoptosis in macrophages via caspase-8-and caspase-3dependent pathways[END_REF], and Leptospira were suggested to induce apoptosis in organs though the caspase-3-dependent pathway in infected mice [START_REF] Marinho | Tissue apoptosis in mice infected with Leptospira interrogans serovar Icterohaemorrhagiae[END_REF]. Thus, TNF-α might play a role in Leptospira-induced apoptosis as it can activate caspase-3-and caspase-8-associated apoptosis [START_REF] Zhao | TNF-alpha stimulates caspase-3 activation and apoptotic cell death in primary septohippocampal cultures[END_REF][START_REF] Wang | TNF-a induces two distinct caspase-8 activation pathways[END_REF]. Kyriakidis et al. reported that TNF-α was the only cytokine found associated with SHPS in leptospirosis patients [START_REF] Kyriakidis | Serum TNF-alpha, sTNFR1, IL-6, IL-8 and IL-10 levels in Weil's syndrome[END_REF]. Alteration of sodium channel was suggested as a cause for the pulmonary damages observed in susceptible Leptospira-infected hamsters [START_REF] Andrade | Leptospirosis leads to dysregulation of sodium transporters in the kidney and lung[END_REF]. Interestingly, TNF-α, together with IL-1β, regulate the expression of sodium channel sub-units in vitro, which could be part of pulmonary damages underlying mechanism [START_REF] Yamagata | The regulation of amiloride-sensitive epithelial sodium channels by tumor necrosis factor-alpha in injured lungs and alveolar type II cells[END_REF].

Pro-inflammatory IL-6 is induced by TNF-α and IL-1β and produced by a large number of immune and non-immune cells. High concentration of IL-6 is an indicator of septic shock and correlates to leptospirosis severity and SPHS [START_REF] Reis | Cytokine response signatures in disease progression and development of severe clinical outcomes for leptospirosis[END_REF][START_REF] Schulte | Cytokines in sepsis: potent immunoregulators and potential therapeutic targets-an updated view[END_REF][START_REF] Papa | Cytokines in human leptospirosis[END_REF]. As TNF-α and IL-1β, IL-6 can also activate the coagulation system, especially in endotoxemic models [START_REF] Schulte | Cytokines in sepsis: potent immunoregulators and potential therapeutic targets-an updated view[END_REF]. This could relate to clinical bleedings, especially in SHPS [START_REF] Haake | Leptospirosis in humans[END_REF], and activation of coagulation [START_REF] Wagenaar | Coagulation disorders in patients with severe leptospirosis are associated with severe bleeding and mortality[END_REF] observed in severe leptospirosis.

High levels of chemokines are found in susceptible hamsters [START_REF] Matsui | Cytokine and chemokine expression in kidneys during chronic leptospirosis in reservoir and susceptible animal models[END_REF], and are associated with organ damage and poor outcome [START_REF] Reis | Cytokine response signatures in disease progression and development of severe clinical outcomes for leptospirosis[END_REF][START_REF] Papa | Cytokines in human leptospirosis[END_REF]. Notably, higher level of CXCL8/IL-8 expression was found in patients with severe clinical signs and was associated with mortality (Wagenaar et al., 2009a,b). Moreover, high levels of adhesion molecules, ICAM-1 or VCAM, are also associated with leptospirosis-induced organ damages [START_REF] Del | Immune receptors and adhesion molecules in human pulmonary leptospirosis[END_REF]. Chemokines along with endothelial adhesion molecules are induced by TNF-α, which promotes leukocytes attraction and extravasation into injured tissue. Their prolonged production can also promote endothelial barrier disruption and diapedesis, which could explain hemorrhages and immune cells infiltrations in tissues associated with severe leptospirosis.

Together with IL-1β, TNF-α promote the activation of immune cells as macrophages, and subsequent secretion of immuno-regulators including pro-inflammatory factors that amplify the inflammatory response. Moreover, high TNF-α and IL-1 circulating levels are considered as the hallmarks of a cytokine storm and their role in sepsis pathophysiology has been largely investigated [START_REF] Schulte | Cytokines in sepsis: potent immunoregulators and potential therapeutic targets-an updated view[END_REF]. These data place TNFα and IL-1β as master conductors of the awry inflammatory response and the subsequent cytokine storm-induced sepsis observed in severe leptospirosis. However, it also emphasizes that these cytokines may not be the best candidates for investigating specific immune responses to a Leptospira infection and for selection of biomarkers for severity prognosis. Genetic studies showing no correlation between TNF-α polymorphisms and leptospirosis outcome are in good accordance with this hypothesis [START_REF] Lingappa | HLA-DQ6 and ingestion of contaminated water: possible geneenvironment interaction in an outbreak of Leptospirosis[END_REF].

Anti-inflammatory and Immunomodulatory Cytokines

Following the onset of a cytokine storm, systemic production of IL-10 is considered as a hallmark of an attempt to restore immunological homeostasis [START_REF] Tisoncik | Into the eye of the cytokine storm[END_REF]. High level of IL-10 in septic patients significantly correlates with sepsis and death suggesting profound immunosuppression [START_REF] Gogos | Pro-versus anti-inflammatory cytokine profile in patients with severe sepsis: a marker for prognosis and future therapeutic options[END_REF]. It also influences the clearance of microorganisms in the host [START_REF] Duell | Recent insights into microbial triggers of interleukin-10 production in the host and the impact on infectious disease pathogenesis[END_REF]. In Lyme borreliosis, a disease due to an infection by another spirochete, Borrelia burgdorferi, contribution of IL-10 in the attenuation of tissue lesions was shown through the modulation of pro-inflammatory cytokines [START_REF] Brown | Dual role of interleukin-10 in murine Lyme disease: regulation of arthritis severity and host defense[END_REF][START_REF] Gautam | Interleukin-10 alters effector functions of multiple genes induced by Borrelia burgdorferi in macrophages to regulate Lyme disease inflammation[END_REF]. Inhibition of endogenous IL-10 also enhanced Borrelia elimination [START_REF] Brown | Dual role of interleukin-10 in murine Lyme disease: regulation of arthritis severity and host defense[END_REF].

In human leptospirosis, controversial results showed either higher levels of IL-10 (Reis et al., 2013;[START_REF] Chirathaworn | Cytokine levels as biomarkers for leptospirosis patients[END_REF] or no significant difference in IL-10 levels (Wagenaar et al., 2009a;[START_REF] Mikulski | Severity markers in severe leptospirosis: a cohort study[END_REF] between mild and severe forms. However, asymptomatic leptospirosis presented an antiinflammatory response with higher IL-10-producing CD4+ Tcells compared to patients with severe or mild leptospirosis [START_REF] Volz | Specific CD4+ T-cell reactivity and cytokine release in different clinical presentations of leptospirosis[END_REF]. Differences in time of sampling might explain this discrepancy. Interestingly, in a murine Cecal Ligation and Puncture (CLP)-induced sepsis model, the inhibition of IL-10 at the time of CLP worsened mortality rate whereas it increased survival when administered 12 h later [START_REF] Song | What is the role of interleukin 10 in polymicrobial sepsis: antiinflammatory agent or immunosuppressant?[END_REF]. Thus, IL-10 contribution in leptospirosis pathophysiology probably depends on the stage and severity of the disease. Altogether, these findings suggest that IL-10 could either be protective by counterbalancing pro-inflammatory cytokines during the early stage of the disease, or have harmful effect in the leptospirosis outcome acting on bacterial burden. Finally, genetic variations could also contribute to the IL-10 dual role since IL-10 promoter FIGURE 1 | Comparison of models of Leptospira infection in resistant and susceptible hosts suggests the importance of the inflammatory response in influencing the disease outcome. In Leptospira-infected mice, the inflammatory response is rapid and strictly regulated. Consequently, homeostasis is maintained as bacteria are rapidly cleared from the blood and no or only mild symptoms develop, which relate to mild leptospirosis observed in 90% of human infections. In Leptospira-infected hamsters, cytokine production is delayed and sustained, which could trigger the onset of a cytokine storm and impair pathogen clearance from the blood. The resulting sepsis-like phenotype could be associated to increased bacterial load, organ failures and hemorrhages found in infected hamsters as well as in severe forms of leptospirosis in humans. (1) Susceptible mouse models (e.g., C3H/HeJ strain) comprise inbred wild-type, immunosuppressed and transgenic mice, used as models for sublethal and lethal leptospirosis (see Gomes-Solecki et al., 2017 for review). ( 2) Comparison of the inflammatory response in resistant vs. susceptible animal models is based on expression profiles found in [START_REF] Matsui | Gene expression profiles of immune mediators and histopathological findings in animal models of leptospirosis: comparison between susceptible hamsters and resistant mice[END_REF]. Expression levels of IL-10 and TNF-α are representative of anti-and pro-inflammatory cytokine production, respectively.

polymorphisms were associated with lower LPS-dependent IL-10 production and with the development of sepsis in patients with major trauma [START_REF] Zeng | Clinical relevance of the interleukin 10 promoter polymorphisms in Chinese Han patients with major trauma: genetic association studies[END_REF].

Inflammatory response is also restricted by regulatory cytokines, as IL-4 or IL-13, promoting T helper (Th) lymphocyte differentiation toward Th2 lineage, suppressing tissue-damaging effects of sustained inflammation [START_REF] Opal | Anti-inflammatory cytokines[END_REF]. Moreover, aberrant production of these cytokines facilitates pathogen invasion during infection [START_REF] Wynn | Type 2 cytokines: mechanisms and therapeutic strategies[END_REF]. IL-4 is induced during leptospirosis with late but massive overexpression in blood from experimentally infected hamsters [START_REF] Vernel-Pauillac | Proinflammatory and immunomodulatory cytokine mRNA time course profiles in hamsters infected with a virulent variant of Leptospira interrogans[END_REF]. Serum levels of IL-4 were also increased in human patients [START_REF] Reis | Cytokine response signatures in disease progression and development of severe clinical outcomes for leptospirosis[END_REF] and frequencies in IL-4 and IL-4R receptor gene polymorphisms were significantly higher in leptospirosis patients compared to healthy subjects [START_REF] Fialho | Role of HLA, KIR and cytokine gene polymorphisms in leptospirosis[END_REF]. Similarly to IL-10, the role of IL-4 in sepsis is still under debate [START_REF] Chousterman | Cytokine storm and sepsis disease pathogenesis[END_REF] Thus, induction of IL-4 and IL-10 might play an important role in leptospirosis pathophysiology that still needs to be precisely described. Indeed, these cytokines could relate to impaired bacterial clearance by restricting pro-inflammatory responses and consequently triggering immunoparalysis related to fulminant septicemia in human leptospirosis [START_REF] Tisoncik | Into the eye of the cytokine storm[END_REF][START_REF] Zhao | The growing spectrum of anti-inflammatory interleukins and their potential roles in the development of sepsis[END_REF].

RESISTANT PHENOTYPE TO LEPTOSPIRA INFECTION: ROLE OF THE IMMUNE RESPONSE

Although hamsters and guinea pigs are suitable models to study acute leptospirosis, the cost of their handling and the lack of experimental tools have limited their use in laboratories. As mentioned above, mice, which are much easier to handle, are resistant to Leptospira infection and become chronic carrier of the bacterium. However, variable degrees of susceptibility have been observed using different mice strains, which allowed scientists to consider mice as suitable models for studying severe leptospirosis. Consequently, a large number of transgenic, mutant, or immunosuppressed mice are now being used as models of chronic, sub-lethal and lethal leptospirosis (see Gomes-Solecki et al., 2017 for review).

Contrasting with delayed and uncontrolled cytokine production observed in susceptible hosts, the inflammatory response in resistant models is characterized by an early but tightly regulated induction of pro-inflammatory cytokines, and a fast and high overexpression of the anti-inflammatory IL-10 (Figure 1). Recently, higher chemokines levels including CCL5/RANTES and CCL8/MCP-2 were quantified in organs from resistant (BALB/c) compared to susceptible (TLR4defective C3H/HeJ) mice 24 h post-infection [START_REF] Domingos | Resistance of mice to Leptospira infection and correlation with chemokine response[END_REF]. Moreover, high expression of chemokines CXCL1/KC, CXCL2/MIP-2, CCL5/RANTES, as well as IL-1β, TNF-α, and IL-10 was observed in sub-lethally infected C3H/HeJ mice [START_REF] Richer | Mouse model for sublethal Leptospira interrogans infection[END_REF][START_REF] Sullivan | Eye-drop inoculation leads to sublethal leptospirosis in mice[END_REF]. This phenotype specificity in the immune response is supported by previous data showing that expression of TNF-α and of CXCL2/MIP-2 chemokine is delayed in organs from susceptible mice [START_REF] Da Silva | Induction of TNF-alfa and CXCL-2 mRNAs in different organs of mice infected with pathogenic Leptospira[END_REF]. Thus, time of induction of chemokines and key cytokines seems to be determinant for the development of a resistant phenotype to Leptospira infection. Moreover, and supporting the possible dual role of IL-10, recent studies reported improved bacterial clearance in mouse kidneys in the absence of IL-10 compared to control animals [START_REF] Devlin | Il-10 deficient mice express IFN-gamma mRNA and clear Leptospira interrogans from their kidneys more rapidly than normal C57BL/6 mice[END_REF][START_REF] Matsui | High level of IL-10 expression in the blood of animal models possibly relates to resistance against leptospirosis[END_REF]. Interestingly, IL-10 deficiency did not affect Leptospira-dependent induction of TNF-α and IL-6 while it enhanced IL-1β and IFNγ overexpression. Thus, IL-10 might inhibit the effective clearance of Leptospira through the early regulation of particular inflammatory cytokines, leading to the persistence of bacteria and allowing chronic carriage in kidneys of resistant animals. It is noteworthy that no clinical signs were observed in Leptospira-infected Il-10 -/-mice [START_REF] Devlin | Il-10 deficient mice express IFN-gamma mRNA and clear Leptospira interrogans from their kidneys more rapidly than normal C57BL/6 mice[END_REF] while IL-10 neutralization led to weight loss in infected OF1 mice [START_REF] Matsui | High level of IL-10 expression in the blood of animal models possibly relates to resistance against leptospirosis[END_REF].

Finally, expression of the anti-inflammatory TGF-β is not modified in the blood [START_REF] Vernel-Pauillac | Differential cytokine gene expression according to outcome in a hamster model of leptospirosis[END_REF][START_REF] Fujita | Comparison of bacterial burden and cytokine gene expression in golden hamsters in early phase of infection with two different strains of Leptospira interrogans[END_REF] while induced in the kidneys [START_REF] Lowanitchapat | Expression of TNF-alpha, TGFbeta, IP-10 and IL-10 mRNA in kidneys of hamsters infected with pathogenic Leptospira[END_REF] from Leptospira-infected hamsters during the acute stage of the disease. Interestingly, renal TGF-β1 expression is downregulated in asymptomatic mice during chronic carriage of Leptospira [START_REF] Matsui | Cytokine and chemokine expression in kidneys during chronic leptospirosis in reservoir and susceptible animal models[END_REF] contrasting with unchanged expression level in fibrotic kidneys from susceptible mice compared to control [START_REF] Fanton D'andon | Leptospira interrogans induces fibrosis in the mouse kidney through Inos-dependent, TLR-and NLR-independent signaling pathways[END_REF][START_REF] Ferrer | Decay-accelerating factor 1 deficiency exacerbates leptospiralinduced murine chronic nephritis and renal fibrosis[END_REF]. Consistently with the pro-fibrotic role of this cytokine in renal fibrogenesis [START_REF] Higgins | TGF-beta1/p53 signaling in renal fibrogenesis[END_REF], and beyond its antiinflammatory effect, this cytokine might specifically participate in renal pathophysiology of leptospirosis.

DISCUSSION

Inflammation is essential for the resolution of microbial infections and involves complex processes that finely coordinate cytokine production. Dysregulation of these mechanisms can trigger cytokine storm and related multi-organ failures as observed during severe leptospirosis and sepsis. Interestingly, the Jarisch-Herxheimer Reaction (JHR) noticed among leptospirosis patients is also characterized by large cytokine overproduction induced by massive bacterial product release consequent to antibiotic treatment [START_REF] Friedland | The Jarisch-herxheimer reaction in leptospirosis: possible pathogenesis and review[END_REF][START_REF] Guerrier | The jarisch-herxheimer reaction in leptospirosis: a systematic review[END_REF][START_REF] Guerrier | Jarischherxheimer reaction among patients with leptospirosis: incidence and risk factors[END_REF]. It is worth noticing that anti-TNF-α antibody therapy was proposed to prevent and ameliorate the JHR [START_REF] Pound | Proposed mechanisms and preventative options of Jarisch-Herxheimer reactions[END_REF][START_REF] Butler | The jarisch-herxheimer reaction after antibiotic treatment of spirochetal infections: a review of recent cases and our understanding of pathogenesis[END_REF]. However, despite the well-established involvement of cytokines in sepsis as observed in severe leptospirosis, no efficient treatment targeting inflammation was clinically validated. Indeed, data obtained from calibrated pre-clinical models can barely be translated to human diseases (van der [START_REF] Van Der Worp | Can animal models of disease reliably inform human studies?[END_REF][START_REF] Mccarron | Exploring the translational disconnect between the murine and human inflammatory response: analysis of LPS dose-response relationship in murine versus human cell lines and implications for translation into murine models of sepsis[END_REF]. Thus, improving knowledge of the host innate immunity in leptospirosis is a major challenge to ameliorate therapeutic approaches, especially in severe forms of leptospirosis that are associated with a dramatic increase in mortality rate.

During Leptospira infection, inflammatory mediators are rapidly regulated in resistant models contrasting with awry production in susceptible hosts, and cytokines were thus proposed as promising biomarkers of the disease outcome in several clinical studies. However, larger and multi-factorial investigations are still required, including cytokine kinetics critical over the course of infection. Unfortunately, in patients, precise time of infection and infecting dose are hardly determined. Moreover, mediators are usually quantified in sera, but specific profiling of host response, including the identification of cellular sources for their production, in altered tissues would necessarily improve our understanding of inflammatory dysfunctions in organs.

Management of severe leptospirosis is also complex due to the diversity of clinical symptoms and immunological profiles found among patients. Human genetic background should be taken into consideration as highlighted by susceptible TLR4 deficient C3H/HeJ mice. However, only a few studies have investigated the correlation between genetic variability and leptospirosis severity and results are still under debate [START_REF] Fialho | Role of HLA, KIR and cytokine gene polymorphisms in leptospirosis[END_REF][START_REF] Esteves | Human leptospirosis: seroreactivity and genetic susceptibility in the population of Sao Miguel Island (Azores, Portugal)[END_REF][START_REF] Cedola | Association of toll-like receptor 2 Arg753Gln and toll-like receptor 1 Ile602Ser single-nucleotide polymorphisms with leptospirosis in an argentine population[END_REF]. Finally, pathogen virulence will inevitably influence the host immune response. Several leptospiral components were described as virulence factors, including genes implicated in motility and LPS synthesis, but also genes whose functions still remain undescribed.

Frontiers in Cellular and Infection Microbiology | www.frontiersin.org

June 2018 | Volume 8 | Article 204

ACKNOWLEDGMENTS

The French Ministry of Research and Technology, Institut Pasteur in New Caledonia, and Institut Pasteur in Paris supported this work. Positions of MM and JC are financed by the Government of New Caledonia.

FUNDING

The research position of MM and JC are financed by the Government of New Caledonia. This program is co-funded by the French Ministry of Research and Technology, Institut Pasteur de Nouvelle-Calédonie, and Institut Pasteur de Paris.

AUTHOR CONTRIBUTIONS

MM drafted the review. JC, SV, and MM contributed to the writing process.

Conflict of Interest Statement:

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.


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Design of Fault-Tolerant and Dynamically-Reconfigurable Microfluidic Biochips*

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Microfluidics-based biochips are soon expected to revolutionize clinical diagnosis, DNA sequencing, and other laboratory procedures involving molecular biology. Most microfluidic biochips are based on the principle of continuous fluid flow and they rely on permanently-etched microchannels, micropumps, and microvalves. We focus here on the automated design of "digital" droplet-based microfluidic biochips. In contrast to continuous-flow systems, digital microfluidics offers dynamic reconfigurability; groups of cells in a microfluidics array can be reconfigured to change their functionality during the concurrent execution of a set of bioassays. We present a simulated annealing-based technique for module placement in such biochips. The placement procedure not only addresses chip area, but it also considers fault tolerance, which allows a microfluidic module to be relocated elsewhere in the system when a single cell is detected to be faulty. Simulation results are presented for a case study involving the polymerase chain reaction.

Early research on CAD for digital microfluidics-based biochips has been focused on device-level physical modeling of single components [6]. While top-down system-level design tools are now commonplace in IC design, no such efforts have been reported for digital microfluidic chips. Here we propose a design methodology that attempts to apply variants of classical module placement techniques to the design of digital microfluidics-based biochips, and thus reduce design time and human effort.

We envisage the following steps in the synthesis of biochips. A behavioral model for a biochemical assay is first generated from the labotorary protocol for that assay. Next, architectural-level synthesis is used to generate a macroscopic structure of the biochip; this structure is analogous to a structural RTL model in electronic CAD. The macroscopic model provides an assignment of assay functions to biochip resources, as well as a mapping of assay functions to timesteps, based in part on the dependencies between them. Finally, geometry-level synthesis creates a physical representation at the geometrical level, i.e., the final layout of the biochip consisting of the configuration of the microfluidic array, locations of reservoirs and dispensing ports, and other geometric details.

Introduction

Microfluidics-based biochips are receiving considerable attention nowadays [START_REF] Verpoorte | Microfluidics meets MEMS[END_REF]. These composite microsystems, which manipulate fluids at nanoliter-to-microliter scales, can greatly simplify cumbersome laboratory procedures. Such lab-on-a-chip devices are therefore expected to facilitate invitro clinical diagnosis, DNA sequencing, and other common procedures in molecular biology.

Most microfluidic biochips of today, consisting of permanently-etched micropumps, microvalves, and microchannels, are based on the principle of continuous fluid flow [START_REF] Verpoorte | Microfluidics meets MEMS[END_REF]. A more promising approach is to manipulate liquids as discrete microdroplets. This novel droplet-based technique is referred to in the literature as "digital microfluidics" [START_REF] Pollack | Electrowetting-based actuation of droplets for integrated microfluidics[END_REF]. Each droplet can be controlled independently and each cell in the microfluidic array has the same structure. In contrast to the continuous-flow systems, digital microfluidics offers dynamic reconfigurability as well as a scalable system architecture [START_REF] Ding | Scheduling of microfluidic operations for reconfigurable two-dimensional electrowetting arrays[END_REF]. Groups of cells can be dynamically reconfigured to change their functionality during the execution of a bioassay. Multiple assays can be concurrently carried out on the microfluidic platform [START_REF] Srinivasan | Clinical diagnostics on human whole blood, plasma, serum, urine, saliva, sweat, and tears on a digital microfluidic platform[END_REF].

Many biochips are expected to be used for safety-critical applications, e.g., patient health monitoring, neo-natal care, and the monitoring of environmental toxins. Therefore, these biochips must be designed to be fault-tolerant such that they can continue to operate reliably in the presence of faults. One approach to fault tolerance is to carefully include spare cells in the array such that faulty cells can be bypassed without any loss of functionality. The locations of the spare cells must be determined by the physical design tool that maps modules to sets of cells in the array.

A key problem in the design of biochips is the placement of microfluidic modules such as different types of mixers and storage units. The ability to reconfigure the microfluidic array during the execution of bioassays makes this placement problem different from the traditional placement problem in electronic design. Furthermore, the placement of the microfluidic modules has a strong impact on the ease of reconfigurability for fault tolerance. Thus, in addition to area (measured by the number of cells in the array), fault tolerance is also a placement criterion. ________________________________ * is research was supported by the National Science Foundation under gr t number IIS-0312352

The complexity of digital microfluidics-based biochips is expected to steadly increase due to the need for multiple and concurrent assays on the chip. Time-to-market and fault tolerance are also expected to emerge as design considerations. As a result, current full-custom design techniques will not scale well for larger designs. There is a need to deliver the same level of CAD support to the biochip designer that is now available to the semiconductor industry. Moreover, it is expected that these microfluidic biochips will be integrated with microelectronic components in nextgeneration system-on-chip designs. The 2003 International

In this paper, we focus on the problem of module placement for digital microfluidics-based biochips with area and fault tolerance as the placement criteria. An example of a real-life biochemical procedure, i.e., polymerase chain Th an reaction (PCR), is used to evaluate the proposed methodology. Since the placement problem is known to be NP-complete [START_REF] Garey | Computers and Intractability-a Guide to the Theory of NP-Completeness[END_REF], a simulated annealing-based heuristic approach is developed to solve the problem in a computationally efficient manner. Solutions for the placement problem can provide the designer with guidelines on the size of the array to be manufactured. If module placement is carried out for a fabricated array, area minimization frees up more cells for sample collection and preparation. We also introduce a simple measure, referred to as the fault tolerance index, to evaluate the fault tolerance capability of the microfluidic biochip; this measure is incorporated into the placement procedure. This procedure leads to small biochip area due to efficient utilization of dynamic reconfigurability, as well as high fault tolerance due to the efficient use of spare cells. biochips is referred to as dynamic reconfigurability, which we exploit here for high fault tolerance. The configurations of the microfluidic array are dynamically programmed into a microcontroller that controls the voltages of electrodes in the array. In this sense, the microfluidic modules (e.g., mixers or storage units) used during the operations can be viewed as reconfigurable virtual devices.

Related Prior Work

The organization of the remainder of the paper is as follows. In Section 2, we present an overview of digital microfluidics-based biochips. Section 3 discusses related prior work. In Section 4, we present a simulated annealing-based heuristic for module placement in dynamically reconfigurable biochips. Next, in Section 5, the reconfiguration technique is studied in more details, and the fault tolerance index, is defined. In Section 6, we incorporate the fault tolerance index in the placement procedure; we then use PCR to evaluate the enhanced placement procedure. Finally, conclusions are drawn in Section 7.

Physical design automation for integrated circuits, especially module placement, is a mature topic [START_REF] Sarrafzadeh | An Introduction to VLSI Physical Design[END_REF]. Heuristics such as simulated annealing are extensively used for custom/macro cell placement; the placement problem is often formulated as 2-D rectangle packing [START_REF] Sechen | VLSI Placement and Global Routing Using Simulated Annealing[END_REF]. Since these techniques do not consider reconfigurability, they are not directly applicable to programmable devices. Dynamically Reconfigurable FPGAs (DRFPGAs) have received much attention recently [START_REF] Bazargan | Fast template placement for reconfigurable computing systems[END_REF]. The partial reconfiguration offered by DRFPGAs is in many ways similar to the dynamic reconfigurability provided by digital microfluidics-based biochips. However, placement techniques reported thus far for DRFPGAs have only targeted the minimization of chip area [START_REF] Bazargan | Fast template placement for reconfigurable computing systems[END_REF]. Fault tolerance has not been considered in these placement techniques. Moreover, the programmability of DRFPGAs is limited by the well-defined roles of interconnect and logic blocks. Interconnect cannot be used for storing information, and logic blocks cannot be used for routing. In contrast, the digital microfluidics-based biochips offer significantly more programmability. The cells in the microfluidic array can be used for storage, functional operations, as well as for transporting fluid droplets.

Background

The operation of digital microfluidics-based biochips is based on the principle of electrowetting actuation. Electrowetting refers to the modulation of the interfacial tension between a conductive fluid and a solid electrode by applying an electric field between them. The basic cell of a digital microfluidics-based biochip is shown in Figure 1(a). The droplet containing biochemical samples, and the filler medium, such as silicone oil, are sandwiched between two parallel glass plates. The bottom plate contains a patterned array of individually controllable electrodes, while the top plate is coated with a ground electrode. A hydrophobic dielectric insulator is added to the plates to decrease the wettability of the surface and to add capacitance between the droplet and the control electrode. By varying the electrical potential along a linear array of electrodes, nanoliter-volume droplets can transport along this line of electrodes. The velocity of the droplet (up to 20cm/s) can be controlled by adjusting the control voltage (0~90V). Microdroplets can therefore be moved freely to any location of a twodimensional array without the need for pumps and valves. Figure 1(b) illustrates a fabricated microfluidic array [START_REF] Pollack | Electrowetting-Based Microactuation of Droplets for Digital Microfluidics[END_REF].

As integrated circuits become denser, reliability emerges as a major challenge. Historically, reliability has been addressed through robust manufacturing processes. However, this approach does not address reliability issues associated with system design. Although microelectromechanical systems (MEMS) is a relatively young field compared to integrated circuits, reliability studies for MEMS have received considerable attention [START_REF] Mccluskey | Design for reliability of micro-electro-mechanical systems (MEMS)[END_REF]. However, due to the significant differences in the actuation principles underlying between digital microfluidics and MEMS, these reliability enhancement techniques cannot be directly used for the design of microfluidics-based biochips. Using a two-dimensional array, many common microfluidic operations for biomedical assays can be performed. For instance, the mixing operation is implemented by routing two droplets to the same location and then turning them around some pivot points. Note that these operations can be performed anywhere on the array during the operation of the biochip, whereas in continuous-flow systems they must operate in a specific permanently-etched micromixer or microchamber. This property of digital microfluidics-based While system-level physical design automation tools are now commonplace in integrated circuit design, no such efforts have been reported for digital microfluidics-based biochips. Some commercial computational fluidic dynamics (CFD) tools, such as CFD-ACE+ from CFD Research Corporation and FlumeCAD from Coventor, Inc. support 3-D simulation of fluidic transport. A recent release of CoventorWare from Coventor, Inc. includes microfluidic behavioral models to support system-level design. Unfortunately, this CAD tool is only able to deal with the continuous-flow systems, and it is therefore inadequate for the design of digital microfluidicsbased biochips.

Recently, a fault classification and a unified test methodology for digital microfluidics-based biochips have been developed [START_REF] Su | Testing of droplet-based microelectrofluidic systems[END_REF]. This cost-effective test methodology facilitates on-line testing, which allows fault testing and biochemical assays to run simultaneously on a microfluidicsbased biochip [START_REF] Su | Concurrent testing of droplet-based microfluidic systems for multiplexed biomedical assays[END_REF].

Module Placement

Placement is one of the key physical design problems for digital microfluidics-based biochips. Based on the results obtained from architectural-level synthesis, i.e., a schedule of bioassay operation, a set of microfluidic modules, and the binding of bioassay operations to modules, placement determines the locations of each module on the microfluidic array in order to optimize some design metrics. Since digital microfluidics-based biochips enable dynamic reconfiguration of the microfluidic array during run-time, they allow the placement of different modules on the same location during different time intervals. Thus, the placement of modules on the microfluidic array can be modeled as a 3-D packing problem. Each microfluidic module is represented by a 3-D box, the base of which denotes the rectangular area of the module and the height denotes the time-span of its operation. The microfluidic biochip placement can now be viewed as the problem of packing these boxes to minimize the total base area, while avoiding overlaps. simulated annealing is that it explores the configuration space of the optimization problem, while allowing hill-climbing moves, i.e., acceptance of new configurations that increase the cost. In this paper, we develop a simulated annealingbased algorithm to solve the placement problem for the digital microfluidics-based biochips. Instead of using a complicated problem-encoding scheme as in [START_REF] Sait | VLSI Physical Design Automation: Theory and Practice[END_REF], our method directly applies the annealing procedure to the actual physical coordinates, sizes, and orientations of microfluidic modules. Since the direct approach cannot guarantee that each new placement is a feasible solution without any forbidden overlap, penalty for such forbidden overlaps is included in the cost function. The algorithm seeks to optimize the design metric while driving the overlap penalty to zero. The pseudocode for this heuristic approach is shown in Figure 3. Some important details of the algorithm are as follows.

Since placement follows architectural-level synthesis in the proposed synthesis flow, the starting times for each operation corresponding to a module, i.e., their positions in the time axis, are pre-determined. Therefore, the 3-D packing problem can be reduced to a modified 2-D placement problem. The horizontal cuts with the 3-D boxes correspond to the configurations of the microfluidic array at different point in time. For example, in Figure 3, the cut t = t 1 corresponds to a 2-D placement shown in Figure 2(b), and the cut t = t 2 corresponds to another configuration in Figure 2(c). The configurations of the microfluidic array during different time intervals can be combined together to form a modified 2-D placement shown in Figure 2(c). Note that the base of the 3-D box representing module i should be placed on the cutting plane t = S i , where S i is the starting time of module i's operation determined by architectural-level synthesis. The modules can arbitrarily slide on these fixed cutting planes while avoiding overlap. Thus, instead of a 3-D packing problem, we only need to consider a modified 2-D placement consisting of several 2-D configurations in different time spans. a) Initial placement: It has been reported in the literature that the initial configuration has little impact on the final outcome of simulated annealing-based optimization [START_REF] Sechen | VLSI Placement and Global Routing Using Simulated Annealing[END_REF]. Therefore, we apply a simple constructive approach to formulate the initial placement, as shown in Figure 4(a). In addition, during the annealing process, the modules are prevented from being placed outside the boundaries of the core area, as defined by Figure 4(a).

The module placement problem for electronic design is known to be NP-complete [START_REF] Garey | Computers and Intractability-a Guide to the Theory of NP-Completeness[END_REF]. The microfluidic placement problem can also be shown by the method of restriction to be NP-complete. Consequently, heuristics are needed to solve the placement problem in a computationally efficient manner. Simulated annealing is a well-studied combinatorial optimization method, and it has been extensively used for traditional module placement problems [START_REF] Sechen | VLSI Placement and Global Routing Using Simulated Annealing[END_REF]. An advantage of b) Generation function: New placements can be generated in several ways: (i) A single microfluidic module is randomly selected to be moved to a randomly-chosen location; (ii) A single module is randomly displaced to a new location and the orientation of this module is changed; (iii) A pair of modules are randomly selected for interchange; (iv) A pair of modules are interchanged in which at least one module has its orientation changed. During the annealing process, we assign the probability p to the single-module displacement and 1 p to the two-module interchange. An effective ratio of p/(1 p) is determined experimentally. c) Controlling window for single-module displacement: The displacement of a single module by a large distance leads to the large increase in the cost metric ( C > 0). At low temperatures during the annealing process, only the new generations with C 0 have a reasonable chance of being accepted. This increases the probability that the displacements over large distances are rejected. We apply a controlling window to discourage long-distance displacements at low temperatures. As the temperature approaches zero, the span of the controlling window reaches its minimum value; this condition is used as the stopping criterion for simulated annealing. d) Annealing scheme: Most annealing parameters are experimentally determined. These include the following: (i) The temperature is modulated as T new = ×T old , where = 0.9; (ii) The number of iterations of the inner loop for a given value of T is determined using the relationship N = Na × Nm, where Na = 400 and Nm is the number of the modules; (ii) The initial temperature T is chosen to ensure that almost every new placement can be accepted, here T = 10000. e) Cost metrics: Cost metrics are used to mathematically represent the optimization goals of the placement problem. We consider the area of the array and the degree of fault tolerance as cost metrics.

Fault Tolerance and Reconfiguration

In this section, we investigate dynamic and partial reconfiguration to avoid a faulty cell in the microfluidic array. Based on this reconfiguration technique, a simple numerical measure, termed fault tolerance index, is defined to estimate the fault tolerance capability of the biochip. We also present an efficient algorithm to determine the fault tolerance index of a biochip configuration based on the notion of maximalempty rectangles.

Partial Reconfiguration

A digital microfluidics-based biochip can be viewed as a dynamically reconfigurable system. If a cell becomes faulty during the operation of the biochip, detected using the technique described in [START_REF] Su | Testing of droplet-based microelectrofluidic systems[END_REF], the microfluidic module containing this cell can easily be relocated to another part of the microfluidic array by changing the control voltages applied to the corresponding electrodes. An example of partial reconfiguration is shown in Figure 4(b). Fault-free unused cells in the array are utilized to accommodate the faulty module. Hence, the configuration of the microfluidic array, i.e., the placement of the microfluidic modules, influences the fault tolerance capability of the biochip. Moreover, since partial reconfiguration only targets the module containing the faulty cell and leaves other aspects of the microfluidic configuration unchanged, a fast heuristic algorithm can be used to find a new location for this module. Therefore, partial reconfiguration is suitable for dynamic on-line reconfiguration during field operation of the microfluidic biochip.

Fault Tolerance Index

In order to facilitate partial reconfiguration and incorporate fault tolerance in the simulated annealing-based placement procedure, we need to evaluate the fault tolerance capability of the microfluidic biochip.

We consider the reconfiguration problem for a single failing cell in the microfluidic array. The single fault assumption is valid when testing and reconfiguration are carried out frequently. We also assume that every cell has the same failure probability. Since microfluidic biochips have not yet been manufactured in large numbers, failure data or statistical models are not readily available, and the assumption of uniform failure probability is reasonable. The failure model can be easily updated when statistical failure data becomes available.

We use a 2-D coordinate system to refer to the cells in the microfluidic array. The bottom-left cell is referred to as (1, 1) and the top-right cell in an m×n array is referred to as (m, n). For an m×n microfluidic array, assume that an arbitrary cell (i, j) is faulty. If this cell is contained in a module for a given microfluidic configuration C, we attempt to apply partial reconfiguration to relocate this module to avoid the faulty cell. If this reconfiguration succeeds, i.e., we find an adequate number of contiguous cells to accommodate this module, or cell (i, j) is not used by any module, we deem this cell to be C-covered for this configuration. Otherwise, cell (i, j) is not C-covered. For an array with k C-covered cells, we define the fault tolerance index (FTI) as follows: FTI = k/(m×n).

Noted that FTI lies between 0 and 1. It increases if there are more C-covered cells in the array. If FTI is 1, it implies that when any single cell in the array is faulty, this microfluidic configuration can be used by applying partial reconfiguration to bypass the faulty cell. On the other hand, if FTI is 0, the biochip cannot be reconfigured if any arbitrary cell becomes faulty. This is the worst case that needs to be avoided.

In order to determine if a cell is C-covered for configuration C, we use an efficient procedure based on the notion of maximal-empty rectangles. The details of this procedure are described below.

Fast algorithm to determine FTI

Our goal is to find maximal-empty rectangles in the microfluidic array, and then check if these rectangles can accommodate the faulty module. A maximal empty rectangle is defined as an empty rectangle (a set of unused cells) that cannot be completely covered by any other empty rectangles. If a maximal-empty rectangle can accommodate the faulty module, this module can be relocated to the empty rectangle to avoid the faulty cell. If no such maximal-empty rectangle exists, partial reconfiguration is deemed to have failed. We then conclude that the corresponding faulty is not C-covered. An encoding method is first used to facilitate the implementation of this algorithm. If a module contains a faulty cell, this module is temporarily removed from the placement. Next the configuration of the microfluidic array is modeled by a matrix consisting of 0s and 1s. The faulty cell and all cells contained in the currently operational modules are represented by 1s; all unused cells are represented by 0s. *: Electrode pitch: 1.5 mm; Gap height: 600 µm In order to find all maximal-empty rectangles rapidly, a data structure, referred to as the staircase [START_REF] Edmonds | Mining for empty spaces in large data sets[END_REF], is employed in the algorithm. A staircase(x, y) is defined as the collection of all overlapping empty rectangles with (x, y) as their bottomright corner.

The data structure staircase(x, y) help to determine all maximal-empty rectangles that lie entirely within the staircase(x, y) and whose bottom-right corner is (x, y). The algorithm traverses the matrix left-to-right and top-to-bottom, creating a staircase for every cell in the matrix. Next, based on the knowledge of staircases, all maximal-empty rectangles are determined. The details underlying the construction of staircases and the generation of the maximal-empty rectangles from staircases are described in [START_REF] Edmonds | Mining for empty spaces in large data sets[END_REF].

Enhanced module placement algorithm

We use a simple greedy algorithm as a baseline for assessing the quality of the proposed placement method. Modules are first sorted in the descending order based on their areas. In each step, the module with the largest area among the unplaced ones is selected and placed at an available bottom-left corner of the array. The total area of the placement generated is 189mm 2 , i.e., it consists of 84 cells, where the pitch of each cell is 1.5mm.

Experimental Evaluation: PCR

Polymerase chain reaction (PCR) is one of the most common techniques for DNA analysis [START_REF] Zhang | Microelectrofluidic Systems: Modeling and Simulation[END_REF]. It is used for rapid enzymatic amplification of specific DNA fragments. PCR can amplify genomic DNA exponentially using temperature cycles. Recently, the feasibility of performing droplet-based PCR on digital microfluidics-based biochips has been successfully demonstrated [START_REF] Pollack | Electrowetting-based actuation of droplets for integrated microfluidics[END_REF]. In this section, we use the mixing stage of PCR as an example to evaluate the simulated annealing-based placement algorithm that facilitates fault tolerance. Its assay protocol can be modeled by a sequencing graph [START_REF] Zhang | Microelectrofluidic Systems: Modeling and Simulation[END_REF], as shown in Figure 5.

Next we apply the placement procedure of Section 4 to this example. First, we consider the minimization of the array area as the only cost metric. The placement generated by the simulated annealing procedure is shown in Figure 7. Its total area is 141.75mm 2 (63 cells), which is 25% less compared to the baseline. The computation takes 5 minutes of CPU time on a 1.0 GHz Pentium-III PC with 256 MB of RAM. Note that some microfluidic modules, e.g., Modules 1 and 3, can use the same cells (via dynamic reconfiguration) when their time-spans do not overlap. Due to the efficient utilization of dynamic reconfigurability, the algorithm leads to a highly compact placement. However, the placement with the minimum array area does not provide adequate fault tolerance. We determine the FTI of the placement shown in Figure 7 using the fast algorithm described in Section 5.3. (The calculation of FTI takes only 1.7 seconds of CPU time.) The FTI of this design is only 0.1270, which implies that only 8 cells in this 7×9 array are C-covered. A microfluidics-based biochip with such a low degree of fault tolerance is not suitable for critical DNA analysis.

Based on this graph model, architectural-level synthesis can be used to carry out both resource binding and scheduling. Let the resource binding be as shown in Table 1. Note that the module generated here has a segregation region wrapped around the functional region, which not only isolates the functional region from its neighbors but also provides a communication path for droplet movement. The data for the operation times associated with the different modules are obtained from real-life experiments [START_REF] Paik | Rapid droplet mixers for digital microfluidic systems[END_REF]. A schedule for the functional operations and module usage is shown in Figure 6.

The goal of the enhanced placement algorithm is to maximize FTI, while keeping the total biochip area small. FTI and area are conflicting criteria, because high FTI often requires a larger biochip area. In our multi-objective placement problem, a solution is a 2-tuple (area, FTI) resulting from a feasible placement of microfluidic modules.

Conclusions

We have presented a simulated annealing-based technique for module placement in microfluidic biochips. The placement criteria include chip area as well as fault tolerance; the latter allows a microfluidic module to be relocated elsewhere in the system when a single cell is detected to be faulty. The placement problem accounts for dynamic reconfigurability of droplet-based microfluidics, whereby groups of cells can be reconfigured to change their functionality during the concurrent execution of a set of bioassays. We have presented simulation results for a case study involving the polymerase chain reaction. This work is expected to facilitate the automated design of biochips, especially since their complexity is expected to grow steadily as they are increasingly used for clinical diagnosis, DNA sequencing, and other laboratory procedures involving molecular biology.

Weighting is a commonly used method for multi-objective optimization. A weight is assigned to each objective according to its relative importance. Next, the different objectives are combined into a single objective using a weighted sum. The solution with the lowest weighted sum is selected. In our problem, weights α and β are assigned to the criteria of area and FTI, respectively. We set α to 1 and adjusted β according to the degree of importance of fault tolerance. The solution with the lowest value of the metric (α×area-β×fault-tolerance number) was considered to be an acceptable solution.

Figure 1 :

 1 Figure 1: (a) Basic cell used in a digital microfluidics-based biochip; (b) A 2-D array for digital microfluidics.

Figure 2 :

 2 Figure 2: Reduction from 3_D placement to a modified 2-D placement. Procedure PLACEMENT /*Simulated Annealing-Based Module Placement */ 1 P = P o ; /* Given initial placement */ 2 T = T ; /* Given initial temperature*/ 3 X = X o ; /* Assign the annealing parameters */ 4 while ("Stopping criterion" is not satisfied) 5 for i = 1: N /* N is the number of iterations of the inner loop */ 6 P new = generate (P); ∆C = cost_metric(P new )-cost_metric(P); 7 r = random(0, 1); /* random(0, 1) is a function that returns a 8 pseudo-random number uniformly distributed on the interval [0, 1] */ 9 if ∆C < 0 or r < exp(-∆C /T) { P = P new ;} 10 end if 11 end for /* end of inner loop */ 12T new = ×T old ; /* updating (cooling) temperature */ 13 end while /* end of annealing procedure */ 14 output the optimal placement P.

Figure 3 :

 3 Figure 3: Simulated annealing-based placement procedure.

Figure 4 :

 4 Figure 4: (a) Initial placement; (b) Example of partial reconfiguration.

Figure 6 :

 6 Figure 6: Schedule highlighting the usage of microfluidic modules.

Figure 7 :

 7 Figure 7: Placement obtained from the simulated annealing-based procedure (7x9=63 cells).Figure 5: Sequencing graph for the mixing stage of PCR.

Figure 5 :

 5 Figure 7: Placement obtained from the simulated annealing-based procedure (7x9=63 cells).Figure 5: Sequencing graph for the mixing stage of PCR.

Table 1 :

 1 Resource binding in PCR.

	Operation	Hardware*	Module	Mixing time
	M1	2x2 electrode array	4x4 cells	10s
	M2	4-electrode linear array	3x6 cells	5s
	M3	2x3 electrode array	4x5 cells	6s
	M4	4-electrode linear array	3x6 cells	5s
	M5	4-electrode linear array	3x6 cells	5s
	M6	2x2 electrode array	4x4 cells	10s
	M7	2x4 electrode array	4x6 cells	3s

Table 2 :

 2 Solutions for different value of β.

	β	10	20	30	40	50	60
	Area (mm 2 )	141.75	157.5	173.25	189.0	204.75	222.75
	FTI	0.2857	0.7143	0.8052	0.8571	0.9780	1.0

Proceedings of the Design, Automation and Test in Europe Conference and Exhibition (DATE'05) 1530-1591/05 $ 20.00 IEEE

Proceedings of the Design, Automation and Test in Europe Conference and Exhibition (DATE'05)

We used a two-stage simulated annealing-based algorithm. In the first stage, a fault-oblivious simulated annealing-based algorithm is used to obtain a placement with the smallest area. Starting from this intermediate configuration, the second stage uses low-temperature simulated annealing (LTSA) to refine the placement in order to enhance fault tolerance. The FTI measure is included in the cost function, while the total area is kept as small as possible. In addition, during LTSA, only single module displacement is performed.


R Thewes

C Paulus

M Schienle

F Hofmann

A Frey

R Brederlow

M Augustyniak

M Jenkner

B Eversmann

P Schindler-Bauer

M Atzesberger

B Holzapfl

G Beer

T Haneder

H.-C Hanke

CMOS-based Biosensor Arrays

CMOS-based sensor array chips provide new and attractive features as compared to today's standard tools for medical, diagnostic, and biotechnical applications. Examples for molecule-and cell-based approaches and related circuit design issues are discussed.

Introduction

Today's availability of highly integrated CMOS circuits on the one hand, and modern miniaturized biotech tools on the other, have had an essential impact on the way we live. In this paper, we consider the potential of merging both disciplines and related on-going developments in the fields of molecule-and cell-based applications.

As an example a simplified flow chart scenario of the drug development process is schematically depicted in Fig. 1. Moreover, CMOS-based solutions also provide a high potential for diagnostic applications.

DNA Microarrays

The purpose of DNA microarray chips [1][2][START_REF]DNA microarrays: a practical approach[END_REF] is the parallel investigation concerning the amount of specific DNA sequences in a given sample. Within predefined positions, single-stranded DNA receptor (probe) molecules are immobilized on the surface of such chips (Fig. 2a)). For application, the whole chip is flooded with a sample containing the target molecules. Complementary (i.e. matching) sequences of probe and target molecules hybridize (Fig. 2d)), whereas that chemical binding process does not occur in case of mismatching strands (Fig. 2e)). Finally, after a washing step, double-stranded DNA is obtained at the match positions (Fig. 2f)), and single-stranded DNA at the mismatch sites (Fig. 2g)). Identification of the sites with double-stranded DNA thus reveals the composition of the sample, since the probes and their positions are known.

Whereas optical detection principles make use of fluorescence or chemoluminescense light originating from label molecules bound to the targets [1][2][START_REF]DNA microarrays: a practical approach[END_REF], electronic principles utilize electrochemically active labels or labels which trigger electrochemical activity to translate hybridization events into charge or current collected by (noble metal) sensor electrodes [START_REF] Hintsche | Frontiers in Biosensorics I[END_REF][START_REF] Bard | [END_REF][START_REF] Paulus | Proc. IEEE Sensors[END_REF]. Alternative labelfree principles are under development. They focus on the effect of impedance or mass changes at the sensors' surfaces after hybridization [START_REF] Mirsky | [END_REF][START_REF] Guiducci | Proc. ESSDERC[END_REF][START_REF] Gabl | Proc. IEEE Sensors[END_REF][START_REF] Brederlow | [END_REF][START_REF] Li | Proc. IEEE Sensors[END_REF].

Using a redox-cycling based technique, CMOS chips have recently been published which detect currents between 1pA and 100nA per sensor [START_REF] Thewes | Advanced Micro and Nano Systems -Enabling Technology for MEMS and Nanodevices[END_REF][START_REF] Schienle | [END_REF]. There, within each sensor site the sensor signal is A/D-converted using a current-to-frequency converting sawtooth generator concept. As shown in Fig. 3, the voltage of the sensor electrode is controlled by a regulation loop via an operational amplifier and a source follower transistor. An integrating capacitor C int is charged by the sensor current.

When the switching level of the comparator is reached, a reset pulse is generated. The measured frequency is approximately proportional to the sensor current. For A/D conversion, the number of reset pulses is counted with a digital counter within a given time frame.

A chip photo of the latest version of such chips using the above described principle is shown in Fig. 4. The chips consist of a 8×16 sensor array including peripheral circuitry (bandgap and current references, auto-calibration circuits, D/A-converters to provide the required voltages for the electrochemical operation) and 6 pin interface for power supply and serial digital data transmission.

Measured electrical, electrochemical, and biological data as well as processing related issues are published elsewhere [START_REF] Thewes | Advanced Micro and Nano Systems -Enabling Technology for MEMS and Nanodevices[END_REF][START_REF] Schienle | [END_REF][14][START_REF] Frey | Proc. ISCAS[END_REF].

Recording from nerve cells and neural tissue

The elementary neural signals of cells, action potentials, are temporal peaks of the intracellular voltage, which are associated with ion currents through the cell membrane. When neurons within a electrolyte are brought in intimate contact with a planar surface, a cleft of order of 60nm between cell membrane and surface is obtained. Ion currents flowing through the cleft lead to a potential drop due to the resistance of the cleft, which can be capacitively probed with an Oxide-Semiconductor-FET (OSFET) below the cleft [START_REF] Bergveld | [END_REF][17][18].

Fig. 5 depicts a CMOS-compatible approach enabling high spatial resolution: The cleft voltage is capacitively coupled to an electrode covered by a thin dielectric and connected to the gate of a standard MOSFET. On this basis, chips with 128×128 positions within a total sensor area of 1mm×1mm are presented in [19]. Since typical neuron diameters are 10µm…100µm the chosen pitch of 7.8µm guarantees that each cell is monitored independent of its individual position. Full frame rate is 2k samples/s.

Circuit design related details are shown in Fig. 6. Selection of a pixel within a row of the array is performed by closing the related switch S 2 . Since the maximum signal amplitudes are between 100µV and 5mV, the sensor MOSFETs (M 1 ) must be calibrated to compensate for the effect of their parameter variations. This is done by closing switch S 1 and forcing a current through M 1 by current source M 2 . After opening S 1 again, a voltage related to the calibration current is stored on the gate of M 1 . This process is periodically performed for all rows in parallel and for all columns in sequence, so that all sensor transistors M 1 within a row provide the same current when selected independent of their individual device parameters.

In the readout mode S 1 is open, S 3 is closed, and M 2 is operated with the same current as in the calibration mode. Action potential induced changes of the sensor electrode potential lead to difference currents between M 1 and M 2 which are compensated by the closed regulation loop composed of A, M 3 , and M 4 and further amplified through the whole signal path shown in Fig. 6. As can be seen, the subsequent current gain stages also undergo a calibration procedure before used for signal amplification.

Measured electrical and biological results, and processing related issues are published elsewhere [START_REF] Hofmann | Proc. ESSDERC[END_REF][START_REF] Lambacher | [END_REF].

Summary

CMOS-based biosensor arrays clearly have proven their feasibility, they open the way to novel and user-friendly highly parallel solutions. One of the remaining challenges is to make commercialization a successful story. [19,[START_REF] Hofmann | Proc. ESSDERC[END_REF] and used in [START_REF] Lambacher | [END_REF].

Fig. 1 :FigFig. 4 :Fig. 5 :

 145 Fig. 1: Schematic diagram depicting the drug-screening process flow aiming to identify one (combination of) compound(s) out of millions of (combinations of)compounds from a library as a suitable drug for a given purpose.

Fig. 3 :

 3 Fig. 3: Circuit principle used for in-sensor site A/D-conversion of the sensor signal based on current-to-frequency conversion[START_REF] Schienle | [END_REF].

Fig. 6 :

 6 Fig.6: Complete signal path of the sensor chip presented in[19,[START_REF] Hofmann | Proc. ESSDERC[END_REF] and used in[START_REF] Lambacher | [END_REF].

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