兽研文章 | 预印文章 Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 Scientific Reports 本预印文章提前共享，以便您更快获取新研究。它可被引用并具有永久DOI。最终编辑版本将自动替换本文。 犬DH82细胞（共）感染利什曼原虫（L. infantum）、塔伦托利什曼原虫及其杂交株的转录组谱和免疫基因表达分析 Maria Stefania Latrofa · Viviane Noll Louzada-Flores · Lucas Cafferati Beltrame · Ciro Leonardo Pierri · Jairo Alfonso Mendoza-Roldan · Domenico Otranto 收稿日期：2026年7月28日 / 接受日期：2026年10月9日 © 作者 2026 摘要 利什曼原虫（L. infantum）和塔伦托利什曼原虫在同域地理区域的共现引发了关于它们在脊椎动物宿主中免疫相互作用的疑问，提示后一物种在犬利什曼病过程中具有保护作用。本研究旨在表征体外感染利什曼原虫（L. infantum）、塔伦托利什曼原虫、其杂交株（即Linf/Ltar）以及同时感染两种利什曼原虫的犬DH82巨噬细胞的转录组谱和细胞因子基因表达。感染后72小时通过RNA-seq分析和RT-qPCR（逆转录qPCR）检测评估感染细胞的转录谱。所有虫株均建立了细胞感染，且寄生虫负荷率随时间点逐渐下降。转录组分析表明，利什曼原虫（L. infantum）（即padj < 0.01；基因数 = 19）和Linf/Ltar杂交株（即padj < 0.01，基因数 = 16）诱导了涉及炎症通路基因的转录变化，而塔伦托利什曼原虫引发较弱反应，与代谢过程相关（即padj > 0.05），反映与巨噬细胞和炎症反应相关基因的转录变化较少。两种利什曼原虫共感染导致最大数量的差异表达基因和最强的炎症通路富集（即padj < 0.01，基因数 = 21）。这些发现进一步得到以下支持：利什曼原虫（L. infantum）（相对倍数变化高达1.13）、Linf/Ltar杂交株（相对倍数变化高达1.30）和两种利什曼原虫共感染（相对倍数变化高达2.26）诱导的中度至强IL-6基因表达，以及塔伦托利什曼原虫相对较高的IL-12基因表达（相对倍数变化高达1.74）。总体而言，结果提供证据表明利什曼原虫（L. infantum）和塔伦托利什曼原虫可能在犬巨噬细胞中诱导不同的转录反应，特别是在与免疫和炎症过程相关的基因中。 关键词 利什曼原虫属 · DH82细胞 · RNA-seq · 关键细胞因子表达
待刊文章《科学报告》https://doi.org/10.1038/s41598-026-75946-7 引言 全球有超过3.5亿人面临利什曼病的风险1，其中利什曼原虫（L. infantum）（动质体目，锥虫科）是这一被忽视的虫媒疾病复合体的主要病原体，仅次于杜氏利什曼原虫。该物种是人兽共患犬利什曼病（CanL）的致病因子，根据白蛉媒介（例如旧世界和新世界的白蛉属和罗蛉属）的存在情况，分布于南美洲和中美洲、西南亚以及地中海盆地2–3。在地中海盆地，其他利什曼原虫物种，如热带利什曼原虫、硕大利什曼原虫、杜氏利什曼原虫和塔伦托利什曼原虫（蜥蜴利什曼原虫亚属），可能与利什曼原虫（L. infantum）共现4–6。特别是塔伦托利什曼原虫，一种与爬行动物相关的非致病性物种，最初在Tarentola mauritanica壁虎中描述7–8，已在与利什曼原虫（L. infantum）共感染的犬、猫和人类中通过分子学和血清学方法检测到7–10。这种共感染发生在无症状犬中，引发了关于塔伦托利什曼原虫在CanL病程中潜在保护作用的疑问。总体而言，GP63（一种毒力因子）的高拷贝数和序列变异性，连同GP63基因家族的成功组装，揭示了塔伦托利什曼原虫该位点广泛的遗传多样性。这种GP63遗传变异性可能影响其功能，影响吞噬作用、逃避补体介导的裂解以及调节宿主免疫应答，从而促进寄生虫在巨噬细胞内的存活11–12。这一基因组特征强化了塔伦托利什曼原虫作为生物技术模型的价值13，并进一步支持其作为替代病原体以及作为针对犬利什曼原虫（L. infantum）感染的免疫预防和免疫治疗方法的候选物的潜在用途13。事实上，体外和体内研究均强调了塔伦托利什曼原虫介导的相互作用可重塑早期先天免疫程序的可能性14,15。此外，塔伦托利什曼原虫在利什曼原虫（L. infantum）流行区的同域存在也引起了研究自然杂交种发生的兴趣，最近有报道称在体外实验室条件下可产生杂交种16，表明它们具有基因组兼容性。事实上，杂交前鞭毛体的转录组在直系同源亲本位点间显示出差异，表明两个基因组之间存在动态相互作用，并伴有基因表达的生物学意义变化16。在利什曼原虫（L. infantum）和塔伦托利什曼原虫杂交株（Linf/Ltar杂交株）中观察到的大规模基因组重构（即染色体丢失、亲本特异性等位基因表达），可能受转录后水平调控，凸显了基因剂量和信使RNA（mRNA）周转的改变，表明一种适应性机制，可能相对于各亲本株影响宿主适应性、组织嗜性和/或毒力等生物学性状18。然而，尽管两种物种之间的体外杂交提供了基因组兼容性的有力证据，杂交株在犬中产生的免疫应答仍有待阐明。本研究旨在验证犬巨噬细胞中塔伦托利什曼原虫感染是否可能影响CanL病程中的先天免疫编程。为此，使用RNA-seq分析了犬巨噬细胞系DH82在单独或联合感染利什曼原虫（L. infantum）或塔伦托利什曼原虫以及Linf/Ltar杂交株后的全局转录应答。此外，通过逆转录酶qPCR（RT-qPCR）评估了同一细胞系中参与CanL的主要促炎和抗炎细胞因子的基因表达。结果 DH82细胞感染动力学和胞内寄生虫负荷 本研究中使用的所有利什曼原虫株均成功感染了DH82细胞（补充图S1），在感染后4至72小时显示出相似且具有统计学显著性（p < 0.05）的时间依赖性感染效率下降，其中利什曼原虫（L. infantum）和共感染观察到最低值（即36.4%的感染巨噬细胞）（图1，补充表1）。同样，在记录到的最高寄生虫/细胞值（即1.55）时
待刊文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 72小时为共感染实验的时间点，所有利什曼原虫虫株的每个细胞寄生虫数随时间推移而下降（图1，补充表2）。感染后4小时，L. tarentolae的感染细胞百分比高于L. infantum，但差异无统计学意义（p > 0.05），且高于Linf/Ltar杂合株（p < 0.05），而Linf/Ltar杂合株与L. infantum无显著差异。共感染组的感染率最高，显著超过L. infantum（p < 0.01）、L. tarentolae（p < 0.05）和杂合株（p < 0.01）。至感染后72小时，L. tarentolae仍保持中等水平但显著高于L. infantum（p < 0.05），而Linf/Ltar杂合株与L. infantum或L. tarentolae均无显著差异。共感染组与L. infantum不再有显著差异。关于每个感染细胞的寄生虫数，在4小时，单独L. infantum显示每个感染细胞的寄生虫负荷最高，显著高于L. tarentolae（p < 0.01）和共感染组（p < 0.05）。Linf/Ltar杂合株与L. infantum无显著差异，共感染组与L. tarentolae亦无显著差异，但显著低于L. infantum（p < 0.01）。至72小时，四种条件下每个感染细胞的寄生虫负荷均未检测到显著差异（图1，补充表2）。图1 利什曼原虫（L. infantum）、塔伦托利什曼原虫及Linf/Ltar杂合株和共感染的感染动态。感染后4小时和72小时的感染细胞百分比及每个感染细胞的寄生虫数。柱上不同字母表示各组内不同时间点之间差异有统计学意义（p < 0.05）。数据以平均值 ± 标准差表示。
待刊文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 DH82细胞对利什曼原虫属感染的转录反应 对DH82巨噬细胞RNA-seq表达谱的主成分分析（PCA）显示，样本按感染条件呈现部分分离（图2a）。共感染样本和未感染对照主要沿PC1正值聚集，而利什曼原虫（L. infantum）、蜥蜴利什曼原虫及Linf/Ltar杂合株感染样本占据部分重叠区域，主要沿PC1负值分布，表明宿主转录谱存在差异，尽管部分重叠。同样，差异表达基因（DEG）分析显示，各感染菌株引起的宿主转录变化存在显著差异，其中共感染（即608个DEG，其中多数376个DEG在感染细胞中下调）和利什曼原虫（L. infantum）（526个DEG，其中多数323个DEG在感染细胞中上调）观察到的数值最高（补充图1、图2b）。交集DEG的维恩图（补充图S3）显示存在大量独特DEG，其中共感染（482个基因）和利什曼原虫（L. infantum）感染巨噬细胞（271个基因）中观察到最高基因表达，表明宿主转录反应强烈。上调DEG的KEGG富集揭示了每种感染条件独特的通路特征。具体而言，利什曼原虫（L. infantum）和Linf/Ltar杂合株（图3a、c）显示转录变化涉及免疫和炎症通路相关基因，包括细胞因子-细胞因子受体相互作用（padj < 0.01，利什曼原虫（L. infantum）基因数=19；padj < 0.01，Linf/Ltar杂合株基因数=16）、白细胞介素17（IL-17）（padj < 0.05，利什曼原虫（L. infantum）基因数=9；padj < 0.01，Linf/Ltar杂合株基因数=7）、磷酸肌醇3-激酶-蛋白激酶B/Akt信号通路（PI3K-Akt，padj < 0.05，Linf/Ltar杂合株基因数=12）以及造血通路，反映了与巨噬细胞和炎症反应相关基因的转录变化。蜥蜴利什曼原虫主要调节代谢通路，细胞因子或核因子κ轻链增强子活化B细胞（NF-κB）信号通路无统计学显著富集（padj > 0.05）（图3b），这与炎症和细胞因子相关通路的转录富集较不明显相一致。相反，共感染表现出最广泛且最显著的转录变化，涉及细胞因子基因（主要为TNF、IL-8和集落刺激因子3 [CSF3]；padj < 0.01且基因数=21）、NF-κB（padj < 0.01且基因数=10）和炎症性疾病通路（即类风湿性关节炎，主要由于细胞因子基因上调）（图3d），表明存在广泛重编程且可能协同的炎症基因表达谱，与单一感染中观察到的不同。图2 感染DH82巨噬细胞的转录组变异和差异基因表达（DGEs）：(a) 感染利什曼原虫（L. infantum）、蜥蜴利什曼原虫、Linf/Ltar杂合株、共感染及其各自未感染对照的DH82细胞RNA-seq表达谱的主成分分析（PCA）。每个点代表一个样本，按条件着色和区分形状。每个点进行三次独立实验重复。(b) 柱状图显示感染后72小时鉴定出的差异表达基因（DEG）总数，包括所有独立实验重复，针对利什曼原虫（L. infantum）、蜥蜴利什曼原虫、Linf/Ltar杂合株和共感染。DEG数值与相应的未感染对照进行比较，使用p ≤ 0.05和|log 2 FC|≥1作为阈值。
预出版文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 尽管与炎症通路相关的基因表达显著富集，对下调KEGG通路的分析显示，利什曼原虫（L. infantum）及Linf/Ltar杂交株（图4a、c）显著抑制了参与抗原加工与呈递（padj < 0.01，基因数 = 6）、吞噬体功能（padj < 0.05，基因数 = 7）和氧化磷酸化（padj < 0.01，基因数 = 10）通路的基因表达，表现为对巨噬细胞效应通路和线粒体通路的抑制。另一方面，蜥蜴利什曼原虫仅引起基因表达的轻度下调，影响少数免疫相关通路（图4b）。共感染细胞显示与类固醇生物合成（padj < 0.01，基因数 = 8）和细胞黏附分子（padj < 0.05，基因数 = 10）相关的基因显著KEGG富集（图4d）。KEGG分析热图（图5）支持上述各感染条件下的转录通路变化，在单独感染利什曼原虫（L. infantum）或共感染的细胞中观察到一致的基因表达上调，涉及：细胞因子–细胞因子受体、IL-17和TNF信号传导、NF-κB、JAK–STAT（Janus激酶/信号转导与转录激活因子）、趋化因子和PI3K–Akt通路及下游效应分子（即IL-1B、CXCL8 [IL-8]、CCL3 [巨噬细胞炎性蛋白-1α，MIP-1α]、CCL4 [MIP-1β]、CCL7 [单核细胞趋化蛋白-3，MCP-3]、CSF3 [集落刺激因子3]、CSF3R [CSF3受体]、白细胞介素受体）。在蜥蜴利什曼原虫感染的细胞中，这些基因的上调很少或未观察到（图5）。关键细胞因子的转录组分析（RNA-seq）显示，共感染和Linf/Ltar杂交株的IL-6信号分别为1.85和1.00 log 2 FC，利什曼原虫（L. infantum）和蜥蜴利什曼原虫分别为1.06 log 2 FC和0.71 log 2 FC。利什曼原虫（L. infantum）的IL-12信号为1.02 log 2 FC，IL-10为0.39 log 2 FC；而蜥蜴利什曼原虫和Linf/Ltar杂交株的IL-12信号分别为1.44和1.39 log 2 FC，IL-10分别为0.15和0.18 log 2 FC。图3 气泡图显示感染以下病原体的DH82巨噬细胞中上调差异表达基因（DEGs）的KEGG通路富集：(a)利什曼原虫（L. infantum）；(b)蜥蜴利什曼原虫；(c)Linf/Ltar杂交株；(d)共感染。气泡大小代表通路中的基因数，气泡颜色表示富集的校正p值。
预出版文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 图5 热图显示感染利什曼原虫（L. infantum）、蜥蜴利什曼原虫、Linf/Ltar杂交株和共感染的DH82巨噬细胞中，所选感兴趣KEGG通路基因的归一化表达（Z分数），并与各自未感染对照进行比较。行对应单个基因，列对应感染条件，均已标注。颜色标尺代表相对表达水平，较高和较低表达以对比色显示（例如红色和蓝色）。通路（如细胞因子–细胞因子受体相互作用、IL-17信号传导、TNF信号传导、NF-κB信号传导、JAK–STAT信号传导、趋化因子信号传导、PI3K–Akt信号传导、Toll样受体信号传导、抗原加工与呈递、吞噬体、补体与凝血级联、造血细胞谱系和代谢通路）根据面板布局进行分组或注释。
图4 气泡图显示感染以下病原体的DH82巨噬细胞中下调差异表达基因（DEGs）的KEGG通路富集：(a)利什曼原虫（L. infantum）；(b)蜥蜴利什曼原虫；(c)Linf/Ltar杂交株；(d)共感染。气泡大小代表通路中的基因数，气泡颜色表示富集的校正p值。
预出版文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 qPCR细胞因子基因表达分析 RT-qPCR分析显示，IL-6基因表达在混合感染条件下最高（2.26 ± 0.08相对倍数变化），单一感染较低（即利什曼原虫（L. infantum）为1.13 ± 0.11相对倍数变化，蜥蜴利什曼原虫为1.00 ± 0.11相对倍数变化；Linf/Ltar杂交株为1.30 ± 0.06相对倍数变化）（图6）。与Linf/Ltar杂交株（分别为1.13 ± 0.44和1.47 ± 0.44相对倍数变化）、利什曼原虫（L. infantum）（0.93 ± 0.09和0.88 ± 0.12相对倍数变化）及混合感染（0.32 ± 0.009和0.90 ± 0.22相对倍数变化）相比，蜥蜴利什曼原虫的IL-4和IL-12表达水平较高（分别为1.35 ± 0.27和1.74 ± 0.31相对倍数变化）（图6）。IL-10基因表达在蜥蜴利什曼原虫中较高（0.68 ± 0.05相对倍数变化），在利什曼原虫（L. infantum）（0.44 ± 0.007相对倍数变化）、Linf/Ltar杂交株（0.59 ± 0.04相对倍数变化）及混合感染（0.57 ± 0.002相对倍数变化）菌株中较低。总体而言，qPCR与RNA-Seq数值在所分析的各基因和实验条件间呈现一致的正相关（Pearson r = 0.914；Spearman相关ρ = 0.839），与感染所用菌株无关（图7）。该相关性支持所观察到的表达模式的一致性。未证实两种方法之间具有等效性或可互换性。图6 感染利什曼原虫（L. infantum）、蜥蜴利什曼原虫、Linf/Ltar杂交株或两种利什曼原虫菌株混合感染的DH82细胞中的细胞因子基因表达。感染后72 h通过RT-qPCR测定IL-4、IL-6、IL-10和IL-12的相对mRNA表达水平。数据以相对倍数变化均值 ± SD表示。
预出版文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 讨论 所获数据表明，用利什曼原虫（L. infantum）和Linf/Ltar杂交株体外感染DH82细胞可诱导与炎性巨噬细胞反应相关的基因表达转录改变，表现为特定感染相关通路的上调（即细胞因子—细胞因子受体相互作用、IL-17、TNF和PI3K-Akt）和下调（抗原加工与呈递、吞噬体功能、氧化磷酸化）。相反，蜥蜴利什曼原虫诱导的转录改变较弱，细胞因子或NF-κB信号表达的富集极少。利什曼原虫（L. infantum）和Linf/Ltar杂交株感染后，归属于氧化磷酸化的基因表达降低，提示DH82细胞在转录水平发生感染相关的代谢重编程，表明线粒体能量代谢可能是巨噬细胞对这些寄生虫反应的相关组成部分。图7 各条件下RT-qPCR与RNA-Seq测量值之间的相关性。显示了所有分析条件的RT-qPCR值（以相对倍数变化表示）和RNA-Seq值（以log₂FC表示）。点颜色表示感染条件（利什曼原虫（L. infantum）、蜥蜴利什曼原虫、Linf/Ltar杂交株、混合感染），点形状表示细胞因子（IL-6、IL-10、IL-12）。叠加线性回归拟合线（黑线），阴影区域表示平均拟合的95%置信区间。两种测量方法之间的正相关采用Pearson相关系数描述（r = 0.914）。未证实两种方法之间具有等效性或可互换性。
预出版文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 总体而言，上述所有转录组学证据表明，Linf/Ltar杂交株所表现的转录模式与感染相关免疫逃逸机制的调节相一致，这正是利什曼原虫（L. infantum）在犬利什曼病（CanL）病程中的典型特征。同时，所观察到的转录谱可能反映了源自蜥蜴利什曼原虫性状的贡献，可能由此导致寄生虫行为的细微差异。这些结果与既往实验一致，即在感染利什曼原虫（L. infantum）的DH82巨噬细胞中记录到相似的免疫通路（即PI3K–Akt、NOD样受体信号、吞噬作用、NF-κB/TNF信号）17。此前已将利什曼原虫（L. infantum）感染细胞中低效的抗寄生虫反应与寄生虫对宿主的株特异性适应相关联17–19，表现为B7/CD80–86分子表达降低，同时对MHC-II产生多变的影响，提示转录重编程，进而导致寄生虫持续存在17–19。如上所述，由Linf/Ltar杂交株诱导的通路相关基因表达与犬细胞中巨噬细胞的转录反应相重叠，小鼠和犬源巨噬细胞的实验感染也支持这一点16。这一观察结果可以用以下事实来解释：蜥蜴利什曼原虫与利什曼原虫（L. infantum）杂交可能改变寄生虫行为（即嗜性、生长特性或抗原组成），同时促进免疫逃逸机制。事实上，最近在意大利北部记录了嗜性的改变，那里报道了一种天然的利什曼原虫（L. infantum）/杜氏利什曼原虫杂交株优先感染人类而非犬20。此外，通过RNA-seq和RT-qPCR在感染两种利什曼原虫物种以及Linf/Ltar杂交株和利什曼原虫（L. infantum）的DH82巨噬细胞中观察到的IL-6转录信号值（即相对倍数变化分别为2.26、1.30和1.13）可能反映了一种能够调节免疫反应的巨噬细胞转录谱，并提示可能影响免疫反应向Th2型偏移14,22。相反，在感染蜥蜴利什曼原虫株（即相对倍数变化1.74）和Linf/Ltar杂交株（即相对倍数变化1.47）后检测到IL-12转录水平升高，提示巨噬细胞对这些寄生虫株存在物种特异性的转录细胞因子反应，并对后续免疫反应具有潜在影响。此前在小鼠和犬体外细胞系统中使用蜥蜴利什曼原虫进行的实验感染也证实了上述观察14,15。由两种利什曼原虫物种共感染诱导的最大DEG集合和最广泛的炎症通路富集（包括TNF-、IL-8和NF-κB相关特征）提示了一种不同于单物种感染后所观察到的转录状态。这种与炎症反应相关的转录本富集支持了蜥蜴利什曼原虫的免疫调节潜力，并提出了其同时存在可能影响巨噬细胞对利什曼原虫（L. infantum）感染转录反应的可能性14,15。总体而言，上述所有观察表明，犬巨噬细胞对蜥蜴利什曼原虫感染的转录谱反应与对利什曼原虫（L. infantum）所观察到的不同。具体而言，这些发现支持以下假说：蜥蜴利什曼原虫与利什曼原虫（L. infantum）相似，可在感染期间调节犬巨噬细胞的转录反应13，尽管两种寄生虫物种之间的基因表达模式存在差异。这些发现应被解释为转录反应的差异，而非不同功能或免疫调节状态的证据。此外，数据强调，利什曼原虫（L. infantum）单独感染、杂交或与蜥蜴利什曼原虫共感染时，均抑制与抗原呈递、吞噬作用、补体功能和更广泛造血信号相关的关键通路的基因表达。尽管不同的转录谱提示蜥蜴利什曼原虫和利什曼原虫（L. infantum）可能在巨噬细胞中诱导不同的转录重编程，并对CanL的发病机制和免疫调节具有潜在影响，但对本研究结果的解释应谨慎，因为所有实验均使用DH82犬巨噬细胞系，可能无法完全反映塑造宿主体内CanL结局的多样性和多细胞免疫串扰。总体而言，还应注意转录组谱是在感染后72小时评估的，代表宿主–寄生虫相互作用的一个特定且相对较晚的阶段。因此，本研究中所鉴定的转录模式应在此时间背景下解释，因为它们可能无法完全捕捉感染全过程中宿主基因表达的动态变化。
预出版文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 尽管未进行蛋白水平验证，这是本研究的一个局限性，但L. tarentolae感染后观察到的独特转录反应，以及Linf/Ltar杂交株诱导的基因表达变化，提示L. tarentolae可能引发独特的巨噬细胞转录状态，进而可能影响后续适应性免疫应答。然而，鉴于这些解释基于转录组学和RT-qPCR数据，因此应被视为潜在生物学过程的提示，而非其功能调节的证据。进一步整合蛋白水平和功能分析的研究将确定这些转录差异是否转化为细胞因子产生或巨噬细胞功能的改变。尽管如此，尽管L. tarentolae的保护性或免疫治疗作用尚需进一步研究，这些数据连同先前报道的L. tarentolae与抗原呈递细胞相互作用并激活其的能力13，可能支持该物种作为开发针对利什曼病创新免疫治疗方法平台的潜力。方法 细胞培养 为提高可重复性并减少变异性，所有感染实验均使用DH82犬巨噬细胞系（CRL-3590，ATCC，美国弗吉尼亚州马纳萨斯）进行。DH82细胞常规维持于Dulbecco改良Eagle培养基（DMEM；Thermo Fisher Scientific，美国马萨诸塞州沃尔瑟姆）中，补充10%热灭活胎牛血清（FBS；Thermo Fisher Scientific，美国马萨诸塞州沃尔瑟姆）和Pen-Strep抗生素（100 U/mL青霉素和100 μg/mL链霉素；Lonza，瑞士巴塞尔），于37 °C、5% CO₂加湿环境中培养。细胞在达到约70–80%汇合度时传代，最多至第三代以尽量减少表型漂移。寄生虫株及培养条件 本研究使用以下虫株：L. infantum MHOM/FR/91/LEM2259（同工酶分型MON-1）和从壁虎分离的L. tarentolae R01123，获自法国蒙彼利埃国际利什曼原虫冷冻保藏与鉴定中心，并先前已用携带耐药盒和荧光标记的整合表达载体标记：pA2-GFP-Neo质粒，携带新霉素耐药盒和绿色荧光蛋白（GFP）荧光标记，用于L. infantum LEM 2259株（Linf-GFP）；pA2-RFP-Hyg载体，携带潮霉素耐药盒和红色荧光蛋白（RFP）报告基因，用于L. tarentolae R011（Ltar-RFP株），按他处所述程序进行14；体外Linf/Ltar杂交株获自上述中心，通过使用两亲本株（Linf-GFP、Ltar-RFP）培养物等体积混合生成，如他处所述14，并含有两种耐药标记（即潮霉素或新霉素）和荧光标记（即GFP、RFP）。前鞭毛体维持于27 °C的Ld1S前鞭毛体（pro）培养基中：M199（编号22350，Gibco）、10% FBS、20 mM HEPES；100 μM腺嘌呤、2 mM L-谷氨酰胺、10 μg/ml叶酸、13.7 μM氯化血红素、4.2 mM NaHCO₃、1×RPMI1640维生素、8 μM 6-生物蝶呤、100单位青霉素和100 μg/ml链霉素，pH 7.4。寄生虫通过定期传代维持，并在一致的晚对数生长期用于感染以尽量减少变异性。感染实验 DH82细胞（每孔2 × 10⁶）接种于六孔板，于37 °C、5% CO₂孵育过夜。感染实验使用L. infantum、L. tarentolae、Linf/Ltar杂交株或L. infantum + L. tarentolae两者共感染的对数期前鞭毛体进行。细胞被每种单独利什曼原虫
预出版文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 虫株和混合虫株以2 × 10⁷寄生虫/ml的浓度感染，在所有感染条件下保持相同的前鞭毛体/巨噬细胞比例。单感染（L. infantum、L. tarentolae和Linf/Ltar杂交株）使用感染复数（MOI）为每个宿主细胞10个寄生虫（1:10，细胞:寄生虫），共感染使用1:5 + 1:5。平板于37 °C、5% CO₂孵育4小时（h）以允许寄生虫内化，然后用磷酸盐缓冲盐水（PBS）（Lonza，瑞士巴塞尔）洗涤两次以去除细胞外寄生虫，随后加入新鲜培养基。对于每孔和每种感染条件，在感染后4 h、8 h、24 h、48 h和72 h通过刮取收集细胞，随后以1350 × g离心10分钟。细胞沉淀保存于裂解缓冲液（RLT，QIAGEN，德国希尔登）中，于-80 °C保存至RNA提取。对于RNA相关实验，细胞以每孔2 × 10⁶ DH82细胞接种于6孔板。对于细胞学染色和基于显微镜的感染定量，细胞以5 × 10⁵接种于含无菌圆形玻璃盖玻片的24孔板中
DH82细胞/孔。每个条件进行三次独立实验重复。显微镜检查、染色和感染定量。对于基于显微镜的感染评估，将生长在24孔板中圆形盖玻片上的DH82细胞固定并使用Diff-Quick ®染色（Merck，Darmstadt，Germany）进行染色。通过计数400个细胞（设复孔）确定感染细胞的百分比和每个细胞的平均寄生虫数。在收获细胞进行RNA提取之前，使用EVOS M5000成像系统（Thermo Fisher Scientific，Waltham，Massachusetts，USA）获取荧光图像，以记录感染相关的形态学特征和荧光信号。RNA提取、测序和转录组分析。使用单个生物学重复进行初步时间进程实验，以评估不同时间点的转录反应并确定显示差异表达基因（DEGs）数量最高的时间点。对感染后72小时收集的细胞进行RNA-seq分析的转录组谱分析，此时观察到相对于未感染对照的最高数量的差异DEGs（补充图S1）。简言之，根据制造商方案使用AllPrep试剂盒（QIAGEN，Hilden，Germany）提取总RNA。通过NanoDrop分光光度法（Thermo Fisher Scientific，Waltham，Massachusetts，USA）测量RNA浓度和纯度。使用2100 Bioanalyzer仪器和RNA Pico芯片（Agilent Technologies，Santa Clara，California，USA）评估RNA完整性数值（RIN）。仅通过预定义QC（质量控制）标准（即OD260/280 ≥ 2.0；OD260/230 ≥ 2.0；RIN ≥ 4.0且浓度超过10 ng/μL）的样品才进行测序处理。RNA测序和生物信息学分析由Novogene（NOVOGENE，UK，Company Limited）进行。简言之，使用poly-T寡核苷酸连接的磁珠对总RNA进行poly(A)选择以富集mRNA。在mRNA片段化后，使用随机六聚体引物合成cDNA。通过末端修复、A加尾、接头连接、大小选择、PCR扩增和纯化生成文库。使用Qubit（Thermo Fisher Scientific，Waltham，Massachusetts，USA）对最终文库进行定量，并使用Bioanalyzer（Agilent Technologies，Santa Clara，California，USA）评估片段大小分布。根据有效浓度和目标数据输出合并文库，并在NovaX- Plus设备（Illumina，San Diego，California，USA）上测序。为了生成干净读数，使用fastp https://github.com/OpenGene/fastp处理原始数据（FASTQ格式），并去除含接头的读数、含poly-N的读数和低质量读数。计算标准测序质量指标，包括Q20、Q30和GC含量，并使用这些高质量读数进行所有下游分析（补充表S3）。使用HISAT2（v2.2.1）（补充表S4）http://daehwankimlab.github.io/hisat-genotype/ 25将干净的双端读数比对到Canis familiaris参考基因组（UU_Cfam_GSD_1.0组装）。比对
预出版文章《Scientific Reports》https://doi.org/10.1038/s41598-026-75946-7 使用StringTie（v2.2.3）https://ccb.jhu.edu/software/stringtie 按样本进行reads组装，26 采用参考引导方法以实现转录本组装和推定新转录本的鉴定。基因水平reads计数使用Feature Counts软件（v2.0.6）https://subread.sourceforge.net/featureCounts.html 生成，27 表达水平以每千碱基转录本每百万片段（FPKM）值汇总。为评估相对基因表达，RNA-seq数据的倍数变化按感染组与未感染对照组之间FPKM值的比值计算，并以log₂倍数变化（log₂FC）表示。在质量控制过程中评估比对率，并在下游差异表达分析前考虑与不同测序批次相关的潜在技术变异。感染组与未感染对照之间的差异基因表达（DGE）分析使用DESeq2软件（v1.42.0）https://bioconductor.org/packages/DESeq2/ 进行，28 基于负二项模型并采用Benjamini–Hochberg错误发现率校正。实验设计中将测序批次作为额外因素纳入，以考虑与不同测序运行相关的潜在变异。基因在校正p值（padj）≤ 0.05且|log2（倍数变化）| ≥ 1时被认为差异表达。差异表达基因的功能富集分析使用Cluster Profiler软件（v4.8.1）https://bioconductor.org/packages/clusterProfiler/ 进行，29 开展京都基因与基因组百科全书（KEGG）和基因本体（GO）通路富集分析，以识别与感染相关转录变化相关的通路 30–32。通过逆转录qPCR评估细胞因子基因表达 使用6 μL总RNA和1x SuperScript™ IV VILO Master Mix（Thermo Fisher Scientific，美国马萨诸塞州沃尔瑟姆）在20 μL逆转录反应中合成cDNA。逆转录在25 °C下进行10 min，随后50 °C下10 min，并在85 °C下酶失活5 min。cDNA浓度使用Qubit™ dsDNA HS Assay Kit（Thermo Fisher Scientific，美国马萨诸塞州沃尔瑟姆）定量，样品保存于− 20 °C直至使用。使用10 μL SsoAdvanced™ Universal Supermix（Bio-Rad，美国加利福尼亚州赫拉克勒斯）和0.7 μL含引物（终浓度400 nM）和探针（250 nM）的PrimerPCR™ Custom Assay进行定量PCR（qPCR）以评估细胞因子基因表达（白细胞介素6，IL-6；白细胞介素10，IL-10；白细胞介素4，IL-4；白细胞介素12，IL-12），基于先前序列并稍作修改 33–35。基因表达水平使用参照基因甘油醛3-磷酸脱氢酶（G3PDH）和先前描述的分析程序进行归一化 19。扩增在以下循环条件下进行：55 °C 2 min，95 °C 10 min，随后45个循环的95 °C 15 s和60 °C 1 min。相对表达使用2 −ΔΔCq方法计算 36，并表示为相对于未感染巨噬细胞的倍数变化，后者用作校准品并赋值为1.0（值> 1 = 表达增加；值< 1 = 表达降低）。基因表达水平按感染与未感染巨噬细胞中基因表达的比值计算，并报告为相对倍数变化。最终值代表每个时间点两次技术重复的中位数。统计数据 统计分析和图表使用GraphPad Prism v. 8.0.0（GraphPad Software，美国加利福尼亚州圣迭戈）进行。使用Shapiro–Wilk检验评估正态数据分布。对每个变量的三次重复进行双因素方差分析，随后进行Tukey事后检验。当p < 0.05时，值被认为具有统计学显著性。补充信息 在线版本包含补充材料，可在https://doi.org/10.1038/s41598-026-75946-7获取。
预出版文章《科学报告》 https://doi.org/10.1038/s41598-026-75946-7 致谢 作者感谢 Isabelle Louradour 博士和 Gerald F. Späth 博士（法国巴斯德研究所）提供 Linf/Ltar 杂交株并对稿件进行审阅。作者贡献 M.S.L.、V.N.L.F. 和 L.C.B. 完成了概念构思、形式分析、数据管理、调查研究、监督、项目管理、可视化。M.S.L.、V.N.L.F.、L.C.B. 完成了形式分析、验证和软件分析；M.S.L.、V.N.L.F. 和 L.C.B. 完成了方法学。J.A.M.R. 提供资源；D.O. 负责经费获取；M.S.L.、V.N.L.F、L.C.B.、C.L.P.、J.A.M.R 和 D.O. 撰写——审阅并编辑稿件。所有作者审阅了稿件。经费 本工作部分得到欧盟委员会在国家研究、创新与竞争力计划——绿色与数字转型（PN RIC 21–27）框架内的支持，2025年3月18日第307号征集，行动1.1.2——支持有限数量的战略研究链——项目名称“监测与分析研究生态系统开发（DOMARE）”MI2615 [CUP B99H26000280007]。研究质量与国际化基金——2024年7月29日第2924号法令”（意大利巴里）。数据可用性 本研究期间生成或分析的数据包含在本已发表文章及其补充信息文件中。生成的原始 RNA-seq 数据已存入序列读取档案库，BioProject PRJNA1348227（识别号 SUB15716407），并存入 Zenodo（DOI 10.5281/zenodo.23242407）。代码可用性 本研究未开发任何算法或软件。RNA-seq 数据处理及下游生物信息学分析使用已建立的公开可用软件完成，包括 fastp、HISAT2、StringTie、featureCounts、DESeq2 和 clusterProfiler。产生的原始数据已提交至 Zenodo（DOI：https://doi.org/10.5281/zenodo.23242407）。声明 利益冲突 作者声明无利益冲突。开放获取 本文依据知识共享署名-非商业性使用-禁止演绎 4.0 国际许可协议授权，允许在任何媒介或格式中以非商业目的使用、共享、分发和复制，前提是您给予原作者和来源适当署名，提供知识共享许可协议的链接，并说明是否对许可材料进行了修改。根据本许可，您无权共享源自本文或其部分的改编材料。本文中的图像或其他第三方材料包含在文章的知识共享许可协议中，除非在材料的署名行中另有说明。如果材料未包含在文章的知识共享许可协议中，且您的预期使用未获法定法规许可或超出许可使用范围，您需要直接从版权持有人处获得许可。要查看本许可协议的副本，请访问 http://creativecommons.org/licenses/by-nc-nd/4.0/。参考文献 1. Alvar, J. 等。全球利什曼病及其发病率全球估计。《PloS one》。7，e35671。https://doi.org/10.1371/journal.pone.0035671（2012）。2. Dantas-Torres, F. 等。旧世界与新世界的犬利什曼病：揭示相似性与差异。《Trends Parasitol》。28，531–538。https://doi.org/10.1016/j.pt.2012.08.007（2012）。3. Morales-Yuste, M.、Martín-Sánchez, J. 和 Corpas-Lopez, V. 犬利什曼病：流行病学、诊断、治疗和预防的最新进展。《Veterinary Sci》。9，387。https://doi.org/10.3390/vetsci9080387（2022）。4. Ntais, P. 等。希腊的利什曼病。《Am. J. Trop. Med. Hyg》。89，906–915。https://doi.org/10.4269/ajtmh.13-0070（2013）。5. Baneth, G.、Zivotofsky, D.、Nachum-Biala, Y.、Yasur-Landau, D. 和 Botero, A. M. 来自人皮肤利什曼病疫点的一只犬的黏膜皮肤利什曼原虫（L. infantum）感染。《Parasit. Vectors》。7，118。https://doi.org/10.1186/1756-3305-7-118（2014）。6. Mendoza-Roldan, J. 等。在利什曼原虫（L. infantum）地方流行的意大利南部，在蜥蜴、白蛉和犬中检测到蜥蜴利什曼原虫：障碍与机遇。《Parasit. Vectors》。14，461。https://doi.org/10.1186/s13071-021-04973-2（2021）。7. Mendoza-Roldan, J. A. 等。蜥蜴利什曼原虫：利什曼病流行病学与控制的新前沿。《Transbound. Emerg. Dis》。69，e1326–e1337。https://doi.org/10.1111/tbed.14660（2022）。
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待刊文章《科学报告》 https://doi.org/10.1038/s41598-026-75946-7 33. Peters, I. R. 等。通过实时逆转录聚合酶链反应对慢性肠病犬十二指肠黏膜细胞因子mRNA进行定量。J. Vet. Intern. Med. 19, 644–653 (2005)。10.1892/0891–6640(2005)19[644:cmqi dm]2.0.co;2。 34. Peters, I. R., Helps, C. R., Calvert, E. L., Hall, E. J. & Day, M. J. 通过实时逆转录聚合酶链反应对慢性肠病犬十二指肠黏膜细胞因子mRNA进行定量。J. Vet. Intern. Med. 19, 644–653 (2005)。10.1892/0891–6640(2005)19[644:cmqidm]2.0.co;2。 35. Siebeler, R., de Winther, M. P. J. & Hoeksema, M. A. 炎症中巨噬细胞干扰素信号传导的调控格局。J. Allergy Clin. Immunol. 152, 326–337. https://doi.org/10.1016/j.jaci.2023.04.022 (2023)。 36. Livak, K. J. & Schmittgen, T. D. 使用实时定量PCR和2(-Delta Delta C(T))方法分析相对基因表达数据。Methods 25, 402–408. https://doi.org/10.1006/meth.2001.1262 (2001)。 出版商注 Springer Nature对已发表地图中的管辖权主张和机构隶属关系保持中立。 作者与隶属机构 Maria Stefania Latrofa 1 · Viviane Noll Louzada-Flores 1,2 · Lucas Cafferati Beltrame 1,3 · Ciro Leonardo Pierri 4 · Jairo Alfonso Mendoza-Roldan 1 · Domenico Otranto 1,5,6 Maria Stefania Latrofa maria.latrofa@uniba.it Domenico Otranto domenico.otranto@uniba.it 1 巴里阿尔多·莫罗大学兽医学系，意大利巴里 2 巴斯德研究所，巴黎西岱大学，INSERM U1201，分子寄生虫学与信号传导研究室，法国巴黎 F-75015 3 杰梅利大学综合医院基金会IRCCS医学与外科科学系，意大利罗马 4 巴里阿尔多·莫罗大学药学系-药物科学，意大利巴里 5 香港城市大学兽医临床科学系，中国香港 6 朱拉隆功大学兽医学院，泰国曼谷
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ARTICLE | Article in Press Scientific Reportshttps://doi.org/10.1038/s41598-026-75946-7 Scientific Reports This Article in Press is shared early to give you faster access to new research. It is citable and carries a permanent DOI. The final edited version will replace it automatically. Transcriptomic profiling and immune gene expression analysis of canine DH82 cells (co)infected by Leishmania infantum, Leishmania tarentolae and their hybrid Maria Stefania Latrofa · Viviane Noll Louzada-Flores · Lucas Cafferati Beltrame · Ciro Leonardo Pierri · Jairo Alfonso Mendoza-Roldan · Domenico Otranto Received: 28 July 2026 / Accepted: 9 October 2026 © The Author(s) 2026 Abstract The co-occurrence of Leishmania infantum and Leishmania tarentolae in sympatric geographic areas raises questions about their immunological interactions in vertebrate hosts, suggesting a protective effect of the latter species in the course of canine leishmaniasis. This study aimed to characterize the transcriptome profile and cytokine gene expression of canine DH82 macrophage cells infected in vitro by L. infantum, L. tarentolae, their hybrid strain (i.e., Linf/Ltar) and with both Leishmania species. The transcriptional profiles of cells infected were assessed at 72 h post-infection by RNA-seq analysis and RT-qPCR (reverse transcriptase qPCR) assay. All strains established cell infection with a progressive decline in parasite burden rate over time points. Transcriptomic analysis indicated that L. infantum (i.e., padj < 0.01; gene count = 19) and Linf/Ltar hybrid strains (i.e., padj < 0.01, gene count = 16) induced a transcriptional changes involving gene of inflammatory pathways, while L. tarentolae elicited a weaker response, associated with metabolic processes (i.e., padj > 0.05), reflecting a less transcriptional changes in genes associated with macrophages and inflammatory responses. The co-coinfection with both Leishmania species resulted in the largest number of differentially expressed genes and the strongest enrichment of inflammatory pathways (i.e., padj < 0.01, gene count = 21). These findings were further supported by moderate to strong IL-6 gene expression induced by L. infantum (up to 1.13 relative fold change), Linf/Ltar hybrid (up to 1.30 relative fold change), and coinfection with both Leishmania species (up to 2.26 relative fold change), as well as by a relatively high IL-12 gene expression (up to 1.74 relative fold change) for L. tarentolae. Overall, the results provided evidence that L. infantum and L. tarentolae may induce distinct transcriptional response in canine macrophages, and particularly in genes associated with immune and inflammatory processes. Keywords Leishmania spp. · DH82 cells · RNA-seq · Key cytokines expression
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 Introduction More than 350 million people are at risk of leishmaniases worldwide 1 , with Leishmania infantum (Kinetoplastida, Trypanosomatidae) representing the main etiological agent of this complex of neglected, vector-borne diseases, after Leishmania donovani. This species is the causative agent of zoonotic canine leishmaniasis (CanL) being distributed worldwide through South and Central America, Southwest Asia and the Mediterranean basin according to the presence of sand fly vectors (e.g., Phlebotomus spp. and Lutzomyia spp. in the Old and New Worlds, respectively) 2–3 . In the Mediterranean basin, other species of Leishmania, such as Leishmania tropica, Leishmania major, L. donovani and Leishmania tarentolae (subgenus Sauroleishmania) may co-occur with L. infantum 4–6 . In particular, L. tarentolae, a reptilian-associated and non-pathogenic species, originally described in Tarentola mauritanica gecko 7–8 was detected, both molecularly and serologically, in dogs, cats and humans coinfected with L. infantum 7–10 . Such a coinfection occurred in asymptomatic dogs raising questions regarding the potential protective effect of L. tarentolae in the course of CanL. Overall, the high copy number and sequence variability of GP63, a virulence factor, together with the successful assembly of the GP63 gene family, reveal extensive genetic diversity in this locus for L. tarentolae. This GP63 genetic variability may affect its function influencing phagocytosis, evasion of complement-mediated lysis, and modulation of the host immune response, thereby promoting parasite survival within macrophages 11–12 . This genomic feature reinforces the value of L. tarentolae as a biotechnological model 13 and further supports its potential use as a surrogate pathogen and as a candidate for immune-prophylactic and immunotherapeutic approaches against L. infantum infection in dogs 13 . Indeed, the possibility that L. tarentolae-mediated interactions can reshape early innate immune programs has been highlighted by both in vitro and in vivo studies 14,15 . Furthermore, the sympatric presence of L. tarentolae in endemic areas for L. infantum also raised interest in investigating the occurrence of natural hybrids, whose creation was recently reported under in vitro laboratory conditions 16 , suggesting their genomic compatibility. Indeed, the transcriptome of hybrid promastigotes displayed differences across orthologous parental loci, indicating a dynamic interplay between the two genomes, accompanied by biologically meaningful changes in gene expression 16 . The substantial genomic restructuring observed in L. infantum and L. tarentolae hybrid strain (Linf/ Ltar hybrid) (i.e., chromosome loss, parent-specific allelic expression), likely regulated at the post-transcriptional level, highlights alterations in gene dosage and messenger RNA (mRNA) turnover, indicating an adaptive mechanism that may influence biological traits such as the host adaptability, tissue tropism and/or virulence, relative to each parental strain 18 . However, though the in vitro hybridization between both species provides strong evidence of genomic compatibility, the immune response generated by hybrid strains in dogs remains to be elucidated. This study aimed to verify whether the infection by L. tarentolae in canine macrophage cells may influence the innate immune programming in the course of CanL. For this purpose, the global transcriptional response of the canine macrophage cell line DH82 was analysed using RNA-seq after infection with L. infantum or L. tarentolae alone or in combination, as well as a Linf/Ltar hybrid. Furthermore, the gene expression of main pro- and antiinflammatory cytokines involved in CanL were assessed via reverse transcriptase qPCR (RT-qPCR) in the same cell line. Results DH82 cell infection dynamics and intracellular parasite burden All Leishmania strains used in this study successfully infected DH82 cells (Supplementary Fig. S1), displaying a similar and statistically significant (p < 0.05) time-dependent decline in infection efficiency from 4 to 72 h post-infection, with the lowest value (i.e., 36.4% of infected macrophages) observed for L. infantum and for coinfection (Fig. 1, Supplementary Table 1). Similarly, the highest value of parasites/cell (i.e., 1.55) recorded at
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 72 h was for the coinfection experiments, with the number of parasites per cell decreasing over time for all Leish‑ mania strains (Fig. 1, Supplementary Table 2). At 4 h post-infection, L. tarentolae showed a higher percentage of infected cells than L. infantum, but not statistically significant (p > 0.05), and than Linf/Ltar hybrid (p < 0.05), while the Linf/Ltar hybrid did not differ significantly from L. infantum. Co-infection resulted in the highest infection rate, significantly exceeding L. infantum (p < 0.01), L. tarentolae (p < 0.05), and the hybrid (p < 0.01). By 72 h post-infection, L. tarentolae remained modest but significantly higher than L. infantum (p < 0.05), while Linf/ Ltar hybrid was not significantly different from either L. infantum or L. tarentolae. Co-infection was no longer significantly different from L. infantum. Regarding parasites per infected cell, at 4 h, L. infantum alone showed the highest parasite burden per infected cell, significantly greater than L. tarentolae (p < 0.01) and the co-infection group (p < 0.05). The Linf/Ltar hybrid did not differ significantly from L. infantum, as well as co-infection from L. tarentolae but was significantly lower than L. infantum (p < 0.01). By 72 h, no significant differences in parasite burden per infected cell were detected among any of the four conditions (Fig. 1, Supplementary Table 2). Fig. 1 Infection dynamics of Leishmania infantum, Leishmania tarentolae, and Linf/Ltar hybrid and coinfection. Percentage of infected cells and parasites per infected cell at 4 and 72 h post-infection. Different letters above bars indicate statistically significant differences between time points within each group (p < 0.05). Data are presented as mean ± SD.
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 DH82 cells transcriptional response to Leishmania spp. infection The principal component analysis (PCA) of RNA-seq expression profiles from DH82 macrophages showed partial separation according to infection condition (Fig. 2a). Coinfected samples and non-infected controls clustered mainly along positive PC1 values, whereas L. infantum, L. tarentolae, and Linf/Ltar hybrid-infected occupied partially overlapping regions, mainly along negative PC1 values, indicating a distinct, although partially overlapping, host transcriptional profiles. Likewise, analysis of DEGs revealed marked differences in the host transcriptional changes among infection strains, with the highest values observed for coinfections (i.e., 608 DEGs, with a majority of 376 DEGs showing downregulation in infected cells) and for L. infantum (526 DEGs, with a majority of 323 DEGs showing upregulation in infected cells) (Supplementary Fig. 1, Fig. 2b). The Venn diagrams of intersectional DEGs (Supplementary Fig. S3) showed a large set of unique DEGs, with highest gene expression observed in coinfected (482 genes) and in L. infantum infected macrophages (271 genes), indicating strong host transcriptional responses. The KEGG enrichment of upregulated DEGs revealed distinct pathway signatures for each infection condition. Specifically, L. infantum and Linf/Ltar hybrid strains (Fig. 3a, c) showed transcriptional changes involving genes associated with immune and inflammatory pathways, including cytokine–cytokine receptor interaction (padj < 0.01, gene count = 19 for L. infantum; padj < 0.01, gene count = 16 for Linf/Ltar hybrid), interleukin 17 (IL-17) (padj < 0.05, gene count = 9 for L. infantum; padj < 0.01, gene count = 7 for Linf/Ltar hybrid), phosphoinositide-3-kinase–protein kinase B/Akt signalling (PI3K-Akt, padj < 0.05, gene count = 12 for Linf/Ltar hybrid), and the hematopoietic pathways, reflecting transcriptional changes in genes associated with macrophage and inflammatory responses. Leishmania tarentolae predominantly modulated metabolic pathways, with no statistically significant enrichment of cytokine or nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signalling (padj > 0.05) (Fig. 3b), consistent with a less pronounced transcriptional enrichment of inflammatory and cytokine-related pathways. Conversely, the coinfection exhibited the broadest and most significant transcriptional changes involving genes of cytokines (mainly TNF, IL-8 and Colony Stimulating Factor 3 [CSF3]; padj < 0.01 and gene count = 21), NF-κB (padj < 0.01 and gene count = 10) and inflammatory disease pathways (i.e., Rheumatoid arthritis, mainly due to the upregulation of cytokines genes) (Fig. 3d), indicating a broadly reprogrammed and potentially synergistic inflammatory gene expression profile distinct from those observed in single infections. Fig. 2 Transcriptomic variation and differential gene expression (DGEs) in infected DH82 macrophages: (a) Principal component analysis (PCA) of RNA-seq expression profiles from DH82 infected with Leishmania infantum, Leishmania taren‑ tolae, Linf/Ltar hybrid strains, coinfection, and their respective non-infected controls. Each point represents one sample, coloured and shaped by condition. Each point was performed in three independent experimental replicates. (b) Bar plot showing the total number of differentially expressed genes (DEGs) identified, at 72 h post-infection including all the independent experimental replicates, for Leishmania infantum, Leishmania tarentolae, Linf/Ltar hybrid strains and coinfection. DEGs values were compared with its corresponding non-infected control, using p ≤ 0.05 and |log 2 FC|≥1 as thresholds.
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 Despite strong enrichment of gene expression associated with inflammatory pathways, analysis of the downregulated KEGG pathways revealed that L. infantum and Linf/Ltar hybrid strains (Fig. 4a, c) markedly suppressed the expression of gene involved in antigen processing and presentation (padj < 0.01 and gene count = 6), phagosome function (padj < 0.05 and gene count = 7) and oxidative phosphorylation (padj < 0.01 and gene count = 10) pathways, as an inhibition of macrophage effector and mitochondrial pathways. On the other hand, L. tarentolae induced only modest downregulation of gene expression, affecting few immune-related pathways (Fig. 4b). Coinfected cells showed significant KEGG enrichment of genes associated with steroid biosynthesis (padj < 0.01 and gene count = 8) and cell adhesion molecules (padj < 0.05 and gene count = 10) (Fig. 4d). Heatmaps of KEGG analyses (Fig. 5) supported the above transcriptional pathway changes across infection conditions, with consistent upregulation of gene expression observed in cells infected by L. infantum alone or coinfected for: cytokine–cytokine receptor, IL-17 and TNF signalling, NF-κB, JAK–STAT (Janus kinase/signal transducer and activator of transcription), chemokine, and PI3K–Akt pathways and downstream effectors (i.e., IL-1B, CXCL8 [IL-8], CCL3 [Macrophage Inflammatory Protein-1α, MIP-1α], CCL4 [MIP-1β], CCL7 [Monocyte Chemotactic Protein-3, MCP-3], CSF3 [Colony Stimulating Factor 3], CSF3R [CSF3 Receptor], interleukin receptors). Little or no upregulation of these gene was observed in L. tarentolae infected cells (Fig. 5). Transcriptomic profiling (RNA-seq) of key cytokines showed IL-6 signal of 1.85 and 1.00 log 2 FC, respectively for coinfection and Linf/Ltar hybrid strains as well as a of 1.06 log 2 FC and of 0.71 log 2 FC for L. infantum and L. tarentolae, respectively. A signal of 1.02 log 2 FC for IL-12 and of 0.39 log 2 FC for IL-10 was observed for L. infantum, whereas L. tarentolae and Linf/Ltar hybrid strains showed a signal of 1.44 and 1.39 log 2 FC, respectively, for IL-12 and of 0.15 and 0.18 log 2 FC, respectively, for IL-10. Fig. 3 Bubble plots showing KEGG pathway enrichment for upregulated differentially expressed genes (DEGs) in DH82 macrophages infected with: (a)Leishmania infantum; (b)Leishmania tarentolae; (c)Linf/Ltar hybrid; (d) coinfection. Bubble size represents the number of genes in the pathway, and bubble colour indicates the adjusted p‑value for enrichment.
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 Fig. 5 Heatmaps showing normalized expression (Z-scores) of genes belonging to selected KEGG pathways of interest in DH82 macrophages infected with Leishmania infantum, Leishmania tarentolae, Linf/Ltar hybrid and coinfection, compared with their respective non-infected control. Rows, correspond to individual genes, and columns to infection conditions, are indicated. Colour scales represent relative expression levels, with higher and lower expressions shown in contrasting colours (e.g. red and blue). Pathways (such as cytokine–cytokine receptor interaction, IL-17 signalling, TNF signalling, NF-κB signalling, JAK–STAT signalling, chemokine signalling, PI3K–Akt signalling, Toll-like receptor signalling, antigen processing and presentation, phagosome, complement and coagulation cascades, hematopoietic cell lineage, and metabolic pathways) are grouped or annotated according to the panel layout.
Fig. 4 Bubble plots showing KEGG pathway enrichment for downregulated differentially expressed genes (DEGs) in DH82 macrophages infected with: (a)Leishmania infantum; (b)Leishmania tarentoale; (c)Linf/Ltar hybrid; (d) coinfection. Bubble size represents the number of genes in the pathway, and bubble colour indicates the adjusted p‑value for enrichment.
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 qPCR cytokine gene expression analysis The RT-qPCR analysis showed the highest value of IL-6 gene expression in coinfection conditions (2.26 ± 0.08 relative fold change) and lower for the single infections (i.e., L. infantum, 1.13 ± 0.11 relative fold change, L. tarentolae, 1.00 ± 0.11 relative fold change; Linf/Ltar hybrid of 1.30 ± 0.06 relative fold change) (Fig. 6). High expression levels of IL-4 and IL-12 were obtained for L. tarentolae (1.35 ± 0.27 and 1.74 ± 0.31 relative fold change, respectively) when compared with that of Linf/Ltar hybrid (1.13 ± 0.44 and 1.47 ± 0.44 relative fold change, respectively), L. infantum (0.93 ± 0.09 and 0.88 ± 0.12 relative fold change) and coinfection (0.32 ± 0.009 and 0.90 ± 0.22 relative fold change) (Fig. 6). IL-10 gene expression was higher for L. tarentolae (0.68 ± 0.05 relative fold change) and lower for L. infantum (0.44 ± 0.007 relative fold change), Linf/Ltar hybrid (0.59 ± 0.04 relative fold change) and for coinfection (0.57 ± 0.002 relative fold change) strains. Overall, qPCR and RNA-Seq values showed a consinsten positive correlation across the analized genes and experimental condition (Pearson r = 0.914; and Spearman correlation ρ = 0.839), irrespective of the strains used for the infection (Fig. 7). This correlation supports concordance in the observed expression patterns. No equivalence or interchangeability between the two methods was demonstrated. Fig. 6 Cytokine gene expression in DH82 cells infected with Leishmania infantum, Leishmania tarentolae, Linf/Ltar hybrid or coinfection with both Leishmania strains. Relative mRNA expression levels of IL-4, IL-6, IL-10, and IL-12 were measured at 72 h post-infection through RT-qPCR. Data are presented as relative fold change mean ± SD.
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 Discussion Data obtained suggest that in vitro infection of DH82 cells with L. infantum and Linf/Ltar hybrid strains induce transcriptional changes of gene expression associated with inflammatory macrophage responses, with up-regulation (i.e., cytokine–cytokine receptor interaction, IL-17, TNF and PI3K-Akt) and down-regulation (antigen processing and presentation, phagosome function, oxidative phosphorylation) of specific infection-related pathways. Conversely, L. tarentolae induced an attenuated transcriptional changes with minimal enrichment of cytokine or NF-κB signal expression. The reduced expression of genes assigned to oxidative phosphorylation following L. infantum and Linf/Ltar hybrid infection suggests infection-associated metabolic reprogramming at the transcriptional level in DH82 cells, identifying mitochondrial energy metabolism as a potentially relevant component of the macrophage response to these parasites. Fig. 7 Correlation between RT-qPCR and RNA-Seq measurements across conditions. The RT-qPCR (expressed as relative fold change) and RNA-Seq (expressed as log₂FC) values are shown for all analysed conditions. Point colour indicates infection condition (Leishmania infantum, Leishmania tarentolae, Linf/Ltar hybrid, coinfection) and point shape indicates cytokine (IL-6, IL-10, IL-12). A linear regression fit is overlaid (black line) and the shaded region indicates the 95% confidence interval for the mean fit. The positive association between the two measurement approaches was described using Pearson’s correlation coefficient (r = 0.914). No equivalence or interchangeability between the two methods was demonstrated.
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 Overall, all the above transcriptomic evidence suggest that the Linf/Ltar hybrid strain exhibits transcriptional patterns consistent with the modulation of immune-evasion mechanisms associated to infection, as is typical for L. infantum in course of CanL. At the same time, the observed transcriptional profile may reflect the contribution of L. tarentolae-derived traits, potentially resulting in subtle differences in parasite behaviour. These results are in line with previous experiments in which a similar immune pathway (i.e., PI3K–Akt, NOD-like receptor signalling, phagocytosis, NF-κB/TNF signalling) was recorded in DH82 macrophages infected by L. infantum 17 . The low effective anti-parasite responses in L. infantum infected cells have been previously correlated to strain-specific adaptation of parasite to the host 17–19 , with a reduced expression of B7/ CD80–86 molecules, alongside with variable effects on MHC-II, suggesting transcriptional reprogramming, and therefore parasite persistence 17–19 . As observed above, the expression of pathway-related genes induced by Linf/ Ltar hybrid overlap the macrophage transcriptional response in canine cells, as also supported by experimental infection in mouse and dog derived-macrophages 16 . Such an observation could be explained by the fact that L. tarentolae hybridised with L. infantum could modify parasite behaviour (i.e., tropism, growth characteristics, or antigenic composition) while promoting immune-evasion mechanisms. Indeed, the change of tropism was recently documented in northern Italy, where a natural L. infantum/L. donovani hybrid was reported infecting preferentially humans, and not dogs 20 . Furthermore, the value of IL-6 transcriptional signal observed by RNA-seq and RT-qPCR in DH82 macrophages infected with both Leishmania species as well as Linf/Ltar hybrid and L. infantum (i.e., 2.26, 1.30 and 1.13 relative fold change) may reflect a transcriptional macrophage profile capable of modulating the immune response and suggesting a potentially influencing the shift of the immune response toward Th2 profile 14,22 . Conversely, elevated IL-12 transcriptional levels detected following infection by strains of L. tarentolae (i.e., 1.74 relative fold change) and Linf/Ltar hybrids (i.e., 1.47 relative fold change) suggesting a species-specific transcriptional cytokine response of macrophages to these parasite strains, with potential implications for subsequent immune response. Previous experimental infections in murine and canine in vitro cell systems with L. tarentolae also corroborate the above observation 14,15 . The largest set of DEGs and the broadest enrichment of inflammatory pathways, including TNF-, IL-8 and NF-κB-associated signatures, induced by coinfection with both Leishmania species, suggests a transcriptional state distinct from those observed following single-species infection. This enrichment of transcripts associated with inflammatory response supports the immunomodulatory potential of L. tarentolae and raises the possibility that its concomitant presence may influence the trabscriptional macrophage response to L. infantum infection 14,15 . Overall, all the above observation suggest that canine macrophages respond to L. tarentolae infection in a distinct trabscriptional profile compared with those observed for L. infantum. Specifically, these findings support the hypothesis in which L. tarentolae, similarly to L. infantum, can modulate transcriptional responses in canine macrophages during infection 13 , although the patterns of gene expression differ between the two parasite species. These findings should be interpreted as differences in transcriptional responses rather than as evidence of distinct functional or immunoregulatory states. Furthermore, the data highlight that L. infantum, alone, hybridized or during coinfection with L. tarentolae, suppresses the gene expression of key pathways associated with antigen presentation, phagocytosis, complement function, and broader hematopoietic signalling. Though the different transcriptional profiles suggest evidence that L. tarentolae and L. infantum may induce a distinct transcriptional reprogramming in macrophage cells with potential implications for pathogenesis and immunomodulation of CanL, the interpretation of the present findings should be taken cautiously, since all experiments used the DH82 canine macrophage cell line may not fully reflect the diverse and multicellular immune crosstalk that shapes CanL outcomes in the host. Overall, it should also be noted that the transcriptomic profile was assessed at 72 h post-infection, representing a specific and relatively late stage of the host–parasite interaction. Thus, the transcriptional patterns identified in the present study should be interpreted within this temporal context, as they may not fully capture the dynamic changes in host gene expression occurring throughout the course of infection.
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 Though protein-level validation was not performed, representing a limitation of this study, the distinct transcriptional response observed following L. tarentolae infection, together with the gene-expression changes induced by the Linf/Ltar hybrid strain, suggest that L. tarentolae may elicit distinct macrophage transcriptional states that may, in turn, influence subsequent adaptive immune responses. However, given that these interpretations were based on transcriptomic and RT-qPCR data, they should therefore be considered as indicative of potential biological processes rather than evidence of their functional modulation. Further investigation integrating protein-level and functional analyses would determine whether these transcriptional differences translate into altered cytokine production or macrophage functions. Nevertheless, though the protective or immunotherapeutic role of L. tarentolae needs further investigation, these data together with the L. tarentolae ability to interact with and activate antigen-presenting cells, previously reported 13 , may support the potential of this species as a platform for the development of innovative immunotherapeutic approaches against leishmaniasis. Methods Cell culture To increase reproducibility and reduce variability, all infection assays were carried out using the DH82 canine macrophage cell line (CRL-3590, ATCC, Manassas, Virginia, USA). DH82 cells were routinely maintained in Dulbecco’s Modified Eagle Medium (DMEM; Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% heat-inactivated fetal bovine serum (FBS; Thermo Fisher Scientific, Waltham, MA, USA) and Pen- Strep antibiotics (100 U/mL of penicillin and 100 μg/mL of streptomycin; Lonza, Basel, Switzerland) and cultured at 37 °C in a humidified atmosphere with 5% CO₂. Cells were passed when achieving ~ 70–80% confluence until maximum their third passage to minimize phenotypic drift. Parasite strains and culture conditions This study used the following strains: L. infantum MHOM/FR/91/LEM2259 (isoenzyme typed MON-1) and L. tarentolae R011 isolated from a gecko 23 received from the International Leishmania Cryobank and Identification Center in Montpellier (France) and previously marked with integrative expression vectors carrying both a resistance cassette and a fluorescence marker: the pA2-GFP-Neo plasmid, carrying a Neomycin resistance cassette and a Green Fluorescent Protein (GFP) fluorescence marker for the L. infantum LEM 2259 strain (Linf-GFP), and the pA2-RFP-Hyg vector, carrying a Hygromycin cassette and an Red Fluorescent Protein (RFP) reporter resistance for L. tarentolae R011 (Ltar-RFP strain), following the procedure elsewhere described 14 ; the in vitro Linf/Ltar hybrid, received from the center above, was generated by using equal volumes of cultures of the two parental strians (Linf-GFP, Ltar-RFP), as elsewhere described 14 , and containing both resistance (i.e., Hygromycin or Neomycin) and fluorescence markers (i.e., GFP, RFP). Promastigotes were maintained at 27 °C in Ld1S promastigote (pro) medium: M199 (ref. 22350, Gibco), 10% FBS, 20 mM HEPES; 100 μM adenine, 2 mM L-glutamine, 10 μg/ml folic acid, 13.7 μM hemin, 4.2 mM NaHCO3, 1xRPMI1640 vitamins, 8 μM 6-biopterin, 100 units penicillin and 100 μg/ml streptomycin, pH 7.4. Parasites were maintained by regular sub-passaging and were used for infections during a consistent late- log growth phase to minimize variability. Infection assays DH82 cells (2 × 10 6 per well) were seeded in six-well plates and incubated overnight at 37 °C and 5% CO 2 . The infection assays were performed with stationary phase promastigotes of L. infantum, L. tarentolae, the Linf/Ltar hybrid, or both L. infantum + L. tarentolae for coinfection. The cells were infected by each individual Leishmania
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 strain and mixed strains at concentration of 2 × 10 7 parasites/ml, maintaining the same proportion of promastigotes/macrophage on all infection conditions. Multiplicity of infection (MOI) of 10 parasites per host cell (1:10, cell: parasite) for single infections (L. infantum, L. tarentolae, and Linf/Ltar hybrid) and of 1:5 + 1:5 for coinfections were used. Plates were incubated at 37 °C, 5% CO₂ for 4 h (h) to allow parasite internalization, then washed twice with phosphate-buffered saline (PBS) (Lonza, Basel, Switzerland) to remove extracellular parasites and fresh medium was added subsequently. For each well and infection condition, cells were collected at 4 h, 8 h, 24 h, 48 h and 72 h post-infection by scraping followed by centrifugation for 10 min at 1350 x g. Cell pellets were then conserved in the lysis buffer (RLT, QIAGEN, Hilden, Germany) at -80 °C until RNA extraction. For RNA-related experiments, cells were seeded in 6-well plates with 2 × 10 6 DH82 cells/well. For cytological staining and microscopy-based infection quantification, cells were seeded in 24-well plates containing sterile round glass coverslips with 5 × 10 5
DH82 cells/well. Each condition was performed in three independent experimental replicates. Microscopy, staining, and infection quantification For microscopy-based assessment of infection, the DH82 cells grown on round coverslips in 24-well plates were fixed and stained using Diff-Quick ® staining (Merck, Darmstadt, Germany). The percentage of infected cells and the mean number of parasites per cell were determined by counting 400 cells in duplicate. Prior to harvesting cells for RNA extraction, fluorescence images were acquired using an EVOS M5000 Imaging System (Thermo Fisher Scientific, Waltham, Massachusetts, USA) to document infection-related morphological features and fluorescence signals. RNA extraction, sequencing and transcriptomic analysis A preliminary time-course experiment was conducted using a single biological replicate to assess the transcriptional response at different time points and identify the time point showing the highest number of differentially expressed genes (DEGs). Transcriptomic profiling by RNA-seq analysis was performed on cells collected at 72 h post-infection when the highest number of differentially DEGs relative to uninfected controls was observed (Supplementary Fig. S1). Briefly, total RNA was extracted using the AllPrep kit (QIAGEN, Hilden, Germany) according to the manufacturer’s protocol. RNA concentration and purity were measured by NanoDrop spectrophotometry (Thermo Fisher Scientific, Waltham, Massachusetts, USA). RNA integrity number (RIN) was assessed using a 2100 Bioanalyzer Instrument with RNA Pico chips (Agilent Technologies, Santa Clara, California, USA). Only samples passing predefined QC (Quality Control) criteria (i.e., OD260/280 ≥ 2.0; OD260/230 ≥ 2.0; RIN ≥ 4.0 and concentration over 10 ng/μL) were processed for sequencing. RNA sequencing and bioinformatics analysis were performed by Novogene (NOVOGENE, UK, Company Limited). Briefly, total RNA was subjected to poly(A) selection using poly-T oligo-attached magnetic beads to enrich for mRNA. Following mRNA fragmentation, cDNA was synthesized using random hexamer primers. Libraries were generated through end repair, A-tailing, adapter ligation, size selection, PCR amplification, and purification. Final libraries were quantified using Qubit (Thermo Fisher Scientific, Waltham, Massachusetts, USA), and fragment size distributions were assessed using a Bioanalyzer (Agilent Technologies, Santa Clara, California, USA). Libraries were pooled according to effective concentration and target data output and sequenced on a NovaX- Plus device (Illumina, San Diego, California, USA). To generate clean reads, the raw data (FASTQ format) were processed with fastp https://github.com/OpenGene/fastp, and adapter-containing reads, reads containing poly-N, and of low-quality were removed. Standard sequencing quality metrics, including Q20, Q30, and GC content, were calculated and all downstream analyses were conducted using these high-quality reads (Supplementary Table S3). Clean paired-end reads were aligned to the Canis familiaris reference genome (UU_Cfam_GSD_1.0 assembly) using HISAT2 (v2.2.1) (Supplementary Table S4)http://daehwankimlab.github.io/hisat-genotype/ 25 . Mapped
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 reads were assembled on a per-sample basis using StringTie (v2.2.3) https://ccb.jhu.edu/software/stringtie, 26 in a reference-guided approach to enable transcript assembly and identification of putative novel transcripts. Genelevel read counts were generated using Feature Counts software (v2.0.6) h t t p s : / / s u b r e a d . s o u r c e f o r g e . n e t / f e a t u r e C o u n t s . h t m l , 2 7 , and expression levels were summarized as fragments per kilobase of transcript per million (FPKM) values. For the assessment of relative gene expression, fold changes for RNA-seq data were calculated as the ratio of the FPKM values between infected and non-infected control groups, and expressed as log₂ fold changes (log₂FC). Mapping rates were evaluated as part of the quality-control procedure, and potential technical variation associated with different sequencing batches was taken into consideration prior to downstream differential expression analysis. Differential gene expression (DGE) analyses between infected groups and uninfected controls were performed using DESeq2 software (v1.42.0) https://bioconductor.org/packages/DESeq2/, 28 , based on a negative binomial model with Benjamini–Hochberg false discovery rate correction. Sequencing batch was included as an additional factor in the experimental design to account for potential variation associated with different sequencing runs. Genes were considered differentially expressed at adjusted p-value (padj) ≤ 0.05 and |log2(fold change)| ≥ 1. Functional enrichment analyses of differentially expressed genes were performed using Cluster Profiler software (v4.8.1) https://bioconductor.org/packages/clusterProfiler/, 29 . Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) pathway enrichment analysis were performed to identify pathways associated with infection-related transcriptional changes 30–32 . Cytokine gene expression evaluation by reverse transcriptase qPCR The cDNA was synthesized in 20 μL reverse-transcription reactions using 6 μL of total RNA and 1x Super- Script™ IV VILO Master Mix (Thermo Fisher Scientific, Waltham, Massachusetts, USA). Reverse transcription was performed at 25 °C for 10 min, followed by 50 °C for 10 min and enzyme inactivation at 85 °C for 5 min. cDNA concentration was quantified using the Qubit™ dsDNA HS Assay Kit (Thermo Fisher Scientific, Waltham, Massachusetts, USA) and samples were stored at − 20 °C until use. Quantitative PCR (qPCR) was performed to assess cytokine gene expression (interleukin 6, IL-6; interleukin 10, IL-10; interleukin 4, IL-4; interleukin 12, IL-12) using 10 μL of SsoAdvanced™ Universal Supermix (Bio-Rad, Hercules, California, USA) and 0.7 μL of PrimerPCR™ Custom Assay containing primers (final concentration 400 nM) and probes (250 nM), based on previously sequences with few modifications 33–35 . Gene expression levels were normalized using the reference gene Glyceraldehyde 3‑phosphate dehydrogenase (G3PDH) and analytical procedures previously described 19 . Amplification was carried out under the following cycling conditions at 55 °C for 2 min, 95 °C for 10 min, followed by 45 cycles of 95 °C for 15 s and 60 °C for 1 min. The relative expression was calculated by using the 2 −ΔΔCq method 36 , and expressed as fold change relative to uninfected macrophages, used as the calibrator and assigned a value of 1.0 (values > 1 = increased expression; values < 1 decreased expression). Gene expression levels are calculated as the ratio between the gene expression in infected versus uninfected macrophages and reported as relative fold change. The final value represents the median of the two technical replicates for each time point. Statistical data Statistical analyses and figures were performed using GraphPad Prism v. 8.0.0 (GraphPad Software, San Diego, CA, USA). Shapiro–Wilk test was used to assess normal data distribution. Two-way ANOVA followed by Tukey’s post hoc test was performed for the triplicates of each variable. Values were considered statistically significant when p < 0.05. Supplementary Information The online version contains supplementary material available at https://doi.org/10.1038/ s41598-026-75946-7.
Article in Press Scientific Reports https://doi.org/10.1038/s41598-026-75946-7 Acknowledgements Authors thank Dr. Isabelle Louradour and Dr. Gerald F. Späth (Institut Psteur, France) for the Linf/ Ltar hybrid strain and for critical reading of the manuscript. Author contributions M.S.L., V.N.L.F. and L.C.B. performed the conceptualization, formal analysis, data curation, investigation, supervision, project administration, visualization. M.S.L., V.N.L.F., L.C.B. performed the formal analysis, validation and soft¬ware analysis; M.S.L., V.N.L.F. and L.C.B. performed the methodology. J.A.M.R. Resources; D.O. was responsible for the funding acquisition; M.S.L., V.N.L.F, L.C.B., C.L.P., J.A.M.R and D.O. Writing – review and edited the manu¬script. All authors reviewed the manuscript. Funding This work was partially supported by the European Commission within the National Research, Innovation and Competitiveness Program for the Green and Digital Transition (PN RIC 21–27), Call DD 307 of 18/03/2025, Action 1.1.2 - Support for a limited number of strategic research chains - Project Title Development of a Research Ecosystem for Monitoring and Analysis (DOMARE) MI2615 [CUP B99H26000280007]. Fondo per la Qualità e l’Internazionalizzazione della Ricerca - D.R. n. 2924 of 29/07/2024” (Bari, Italy). Data availability Data generated or analyzed during this study are included in this published article and its supplementary information files. Raw RNA-seq data generated were deposited in the Sequence Read Archive under BioProject PRJNA1348227 (Identification number SUB15716407) and in Zenodo (DOI.(DOI 10.5281/zenodo.23242407). Code availability No algorithms or software were developed for this study. RNA-seq data processing and downstream bioinformatic analyses were performed using established, publicly available software, including fastp, HISAT2, StringTie, featureCounts, DESeq2, and clusterProfiler. The raw data produced was submitted in Zenodo (DOI: h t t p s : / / d o i . o r g / 1 0 . 5 2 8 1 / z e n o d o . 2 3 2 4 2 4 0 7 ) . Declarations Competing interests The authors declare no competing interests. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit h t t p : / / c r e a t i v e c o m m o n s . o r g / l i c e n s e s / b y - n c - n d / 4 . 0 / . References 1. Alvar, J. et al. Leishmaniasis worldwide and global estimates of its incidence. PloS one. 7, e35671. h t t p s : / / d o i . o r g / 1 0 . 1 3 7 1 / j o u r n a l . p o n e . 0 0 3 5 6 7 1 (2012). 2. Dantas-Torres, F. et al. Canine leishmaniosis in the Old and New Worlds: unveiled similarities and differences. Trends Parasitol. 28, 531–538. https://doi.org/10.1016/j.pt.2012.08.007 (2012). 3. Morales-Yuste, M., Martín-Sánchez, J. & Corpas-Lopez, V. Canine Leishmaniasis: Update on Epidemiology, Diagnosis, Treatment, and Prevention. Veterinary Sci. 9, 387. https://doi.org/10.3390/vetsci9080387 (2022). 4. Ntais, P. et al. Leishmaniases in Greece. Am. J. Trop. Med. Hyg. 89, 906–915. https://doi.org/10.4269/ajtmh.13-0070 (2013). 5. Baneth, G., Zivotofsky, D., Nachum-Biala, Y., Yasur-Landau, D. & Botero, A. M. Mucocutaneous Leishmania tropica infection in a dog from a human cutaneous leishmaniasis focus. Parasit. Vectors. 7, 118. h t t p s : / / d o i . o r g / 1 0 . 1 1 8 6 / 1 7 5 6 - 3 3 0 5 - 7 - 1 1 8 (2014). 6. Mendoza-Roldan, J. et al. Detection of Leishmania tarentolae in lizards, sand flies and dogs in southern Italy, where Leishmania infantum is endemic: hindrances and opportunities. Parasit. Vectors. 14, 461. h t t p s : / / d o i . o r g / 1 0 . 1 1 8 6 / s 1 3 0 7 1 - 0 2 1 - 0 4 9 7 3 - 2 (2021). 7. Mendoza-Roldan, J. A. et al. Leishmania tarentolae: A new frontier in the epidemiology and control of the leishmaniases. Transbound. Emerg. Dis. 69, e1326–e1337. https://doi.org/10.1111/tbed.14660 (2022).
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