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Used samples (Manuscript_Marius_Karoline_2026)

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分析脚本与论文图表的映射

🔹 Group3 vs Group4 分析

脚本：MicrobiotaProcess_PCA_Group3-4.R
对应图表：论文 图 4A–C

图号 内容 分析方法
4A 实验设计示意图 –
4B PCoA 图（Bray-Curtis 距离） mp_cal_pcoa() + mp_plot_ord()
4C 差异丰度 OTU 气泡图 DESeq2 + 气泡图可视化

该分析比较的是老年雄性 vs 老年雌性小鼠的稳态肠道微生物组成

🔹 Group9_10_11 vs pre-FMT 分析

脚本：MicrobiotaProcess_Group9_10_11_PreFMT.R + Phyloseq_Group9_10_11_pre-FMT.Rmd
对应图表：论文 图 5B、5C、5D、5E

图号 内容 分析方法
5B FMT 后受体小鼠的 PCoA 图 mp_cal_pcoa() + mp_plot_ord()
5C 科水平相对丰度堆叠图 mp_plot_abundance(taxa.class = Class)
5D 差异丰度 OTU 气泡图（FMT 组间比较） DESeq2/LEfSe + 气泡图
5E 脑内 IL-17A⁺ γδ T 细胞流式定量 流式细胞术 + 统计检验

该分析验证粪便微生物移植（FMT）对年轻受体小鼠卒中后免疫反应的影响

✅ 关键分析要点确认

  1. 距离矩阵：均使用 Bray-Curtis + Hellinger 转换
  2. 统计检验：PERMANOVA (mp_adonis) + 事后两两比较
  3. 可视化：mp_plot_ord 用于序贯图，mp_plot_abundance 用于组成图
  4. 输出格式：PNG/PDF/SVG 多格式保存，便于论文投稿
  • 🔍 检查某段代码的逻辑或参数设置？
  • 📊 解释某个统计结果（如 PERMANOVA 的 R²、p 值）？
  • 🎨 优化图表的美学参数（颜色、字体、图例）？
  • 📝 撰写方法部分或图注的英文描述？

🐭 实验小鼠组别详解（中文版）

以下是本研究中使用的全部 14 个实验组别的详细说明，按功能分类整理：

🔹 第一类：中风模型组（用于图 4 和补充图 3）

组号 样本前缀 完整样本 性别/年龄 状态 用途
1 sample-A* A1–A11 ♂ 老年 中风后 3 天 图 4D–F（血液/脑组织 SCFA 检测）
2 sample-B* B1–B16 ♀ 老年 中风后 3 天 图 4D–F（血液/脑组织 SCFA 检测）

📌 说明：这两组用于比较中风后老年雄性和雌性小鼠的微生物代谢物（短链脂肪酸）水平差异。

🔹 第二类：基线供体组（用于图 4、补充图 4、图 5C）

组号 样本前缀 完整样本 性别/年龄 状态 用途
3 sample-C* C1–C10 ♀ 老年 基线，FMT 供体 图 4A–C（16S 测序）、补充图 4、图 5C（Boxplot 3）
4 sample-E* E1–E10 ♂ 老年 基线，FMT 供体 图 4A–C（16S 测序）、补充图 4、图 5C（Boxplot 2）
5 sample-F* F1–F5 ♂ 年轻 基线，FMT 供体 对照供体，未在主图中展示

📌 关键说明：

  • 组 3 和组 4 是粪菌移植（FMT）的供体小鼠，用于提供老年雌/雄肠道菌群
  • 图 4 和补充图 4 中实际使用的样本为：♀供体 C1–C6（n=6），♂供体 E1–E8（n=8），其余样本因年龄偏小或测序深度不足被排除

🔹 第三类：FMT 预处理组（用于图 5B 紫色点）

组号 样本前缀 完整样本 性别/年龄 状态 用途
6 sample-G* G1–G6 ♂ 老年 FMT 前，抗生素处理前，批次 I 图 5B（紫色，pre-FMT 基线）
7 sample-H* H1–H6 ♀ 老年 FMT 前，抗生素处理前，批次 I 图 5B（紫色，pre-FMT 基线）
8 sample-I* I1–I6 ♂ 年轻 FMT 前，抗生素处理前，批次 II 图 5B（紫色，pre-FMT 基线）

📌 说明：这三组合并为”pre-FMT”基线组（n=18），代表年轻雄性受体小鼠在接受粪菌移植之前的肠道菌群状态。

🔹 第四类：FMT 受体组（用于图 5）

组号 样本前缀 完整样本 性别/年龄 接受供体 状态 用途
9 sample-J* J1–J4, J10, J11 ♂ 年轻 老年♂供体 FMT 后，中风前 图 5B🔵、5C（Boxplot 4）、5D、5E
10 sample-K* K1–K6 ♂ 年轻 老年♀供体 FMT 后，中风前 图 5B🔴、5C（Boxplot 5）、5D、5E
11 sample-L* L2–L6 ♂ 年轻 年轻♂供体 FMT 后，中风前 图 5B🟢、5E（对照）

📌 关键说明：

  • 所有受体均为年轻雄性小鼠，仅供体来源不同
  • “aged♂ FMT” = 接受老年雄性供体粪便的年轻受体（不是受体本身是老年！）
  • 图 5C 的 5 个箱线图 = pre-FMT 基线 + 2 个供体组 + 2 个受体组（不含年轻♂供体受体组）

🔹 第五类：FMT + 中风后组（未在主图展示）

组号 样本前缀 完整样本 性别/年龄 接受供体 状态 用途
12 sample-M* M1–M8 ♂ 老年 老年♂供体 FMT 后，中风后 补充分析
13 sample-N* N1–N10 ♀ 老年 老年♀供体 FMT 后，中风后 补充分析
14 sample-O* O1–O8 ♂ 年轻 年轻♂供体 FMT 后，中风后 补充分析

📌 说明：这三组用于探索性分析，未出现在主论文图表中。

🧭 快速记忆口诀

✅ "FMT 标签 = 供体特征，不是受体特征"
   • aged♂ FMT = 供体是老年雄性
   • 受体永远是年轻雄性（本实验设计）

✅ 图 4 = 老年供体（组 3/4）+ 老年中风小鼠（组 1/2）
✅ 图 5 = FMT 实验：受体（组 6–11）+ 供体（组 3/4）
✅ 补充图 4 = 仅老年供体（组 3/4，筛选后 C1–C6, E1–E8）

⚠️ 样本排除说明

组别 排除样本 排除原因
组 3（♀供体） C7, C8, C9, C10 C8–C9 年龄偏小；C10 为离群值/测序深度低
组 4（♂供体） E9, E10 测序深度低/离群值
组 9（受体） J5, J6, J7, J8, J9 测序深度不足或质量控制排除
组 10（受体） K7–K15 测序深度不足或质量控制排除
组 11（受体） L1, L7–L15 测序深度不足或质量控制排除

📌 最终用于分析的样本数以各图图例标注为准（如：图 5 中 aged♂ FMT n=6, aged♀ FMT n=6）

TODO: 导出完整的样本–组别映射 CSV 文件，or 提供某张图的精确样本列表🎯

关于 “aged♂ FMT” 的明确解释

aged♂ FMT = 接受了老年雄性供体粪便的年轻雄性受体小鼠

🔹 实验设计核心逻辑

角色 年龄/性别 说明
受体（接受粪便） 🐭 年轻雄性（4周龄起始） 所有 FMT 组的受体都是相同的年轻雄性小鼠
供体（提供粪便） 🐭 老年雄性 / 老年雌性 / 年轻雄性 供体的年龄/性别是实验变量

🔹 样本分组详解

🟣 Purple (pre-FMT, n=18): G1–G6, H1–H6, I1–I6
   → FMT前的基线年轻雄性小鼠（未接受移植）

🔵 Blue (aged♂ FMT, n=6): J1, J2, J3, J4, J10, J11
   → 年轻雄性受体 + 接受【老年雄性】供体粪便

🔴 Red (aged♀ FMT, n=6): K1–K6
   → 年轻雄性受体 + 接受【老年雌性】供体粪便

🟢 Green (young♂ FMT, n=5): L2–L6
   → 年轻雄性受体 + 接受【年轻雄性】供体粪便（对照组）

🔹 文献依据

来自 260311_LTPaper.pdf Figure 5 图例：

“Principal coordinates analysis (PCoA) of young male mice before (purple) (n=18), and after FMT of aged male (n=6) (blue) or female (n=6) (red) or young male (n=5) (green) stool donors.”

→ 明确说明分析对象是 young male mice，括号内描述的是 stool donors（粪便供体）的特征。

来自 Supplemental Methods “Microbiota eradication and FMT”：

“4 weeks old male mice were treated for 2 weeks with an antibiotic cocktail… recipient mice were gavaged with donor stool four times over two weeks.”

→ 受体小鼠起始年龄为 4周龄（年轻）。

Figure 5 小标题：

“FMT of aged male microbiota increases IL-17A-producing γδ T cells in the post-ischemic brain of young recipient mice“

→ 再次确认受体是 young recipient mice。

🔹 为什么这样设计？

这个实验的核心科学问题是：

“供体微生物的年龄/性别特征，能否通过移植’传递’给受体，并影响受体的免疫反应？”

通过保持受体一致（年轻雄性），仅改变供体来源，可以：

  1. 排除受体自身年龄/性别的混杂效应
  2. 直接评估供体微生物对受体免疫表型（如 IL-17A⁺ γδ T 细胞）的因果影响
  3. 验证”微生物介导的年龄/性别差异”假说

✅ 快速记忆口诀

“FMT 标签 = 供体特征，不是受体特征”

  • aged♂ FMT = 供体是老年雄性
  • 受体永远是年轻雄性（本实验中）

🔹 Figure 5B: PCoA of FMT Experiment

“Principal coordinates analysis (PCoA) of young male mice before (purple) (n=18), and after FMT of aged male (n=6) (blue) or female (n=6) (red) or young male (n=5) (green) stool donors.”

  • 🟣 Purple (pre-FMT, n=18): Groups 6+7+8 → G1–G6, H1–H6, I1–I6
  • 🔵 Blue (aged♂ FMT, n=6): Group9 → J1, J2, J3, J4, J10, J11
  • 🔴 Red (aged♀ FMT, n=6): Group10 → K1–K6
  • 🟢 Green (young♂ FMT, n=5): Group11 → L2–L6 (L1, L7–L15 excluded for low depth/QC)

🔹 Figure 5C=Figure 5B+C1-7+E1-10 (Need to be confirmed?): Family-Level Relative Abundance Boxplots (5 panels)

Based on your co-author’s note: “Figure 5C uses the Figure 5B recipient samples PLUS the aged donor samples (Groups 3 & 4).”

  • Boxplot 1 (pre-FMT baseline, n=18): Groups 6+7+8 → G1–G6, H1–H6, I1–I6
  • Boxplot 2 (aged♂ stool donors, n=8): Group4 → E1–E10
  • Boxplot 3 (aged♀ stool donors, n=6): Group3 → C1–C7
  • Boxplot 4 (aged♂ FMT recipients, n=6): Group9 → J1, J2, J3, J4, J10, J11
  • Boxplot 5 (aged♀ FMT recipients, n=6): Group10 → K1–K6
  • !!No Group11 (L2-L6)!!

⚠️ Key difference: Group11 (young♂ FMT recipients, L2–L6) is shown in Figure 5B but is NOT included in Figure 5C, since Figure 5C focuses on comparing the effect of aged donor microbiota.

🔹 Figure 5D: Bubble Plot of Differentially Abundant Taxa (DESeq2)

“Bubble plot showing differentially abundant Operational Taxonomic Units (OTUs) between young male recipients of aged female vs. aged male FMT. x-axis = log₂ fold change, y-axis = bacterial family, bubble size = adjusted p-value, color = bacterial order.”

  • 🔵 Aged♂ FMT recipients (Group9, n=6): J1, J2, J3, J4, J10, J11 → Reference group (log₂FC < 0 = enriched in this group)
  • 🔴 Aged♀ FMT recipients (Group10, n=6): K1–K6 → Comparison group (log₂FC > 0 = enriched in this group)
Key families highlighted in the plot: Direction Family (Order) Enriched in Biological note
🔴 Positive log₂FC Lachnospiraceae (Clostridiales) Aged♀ FMT SCFA producer
🔴 Positive log₂FC Ruminococcaceae (Clostridiales) Aged♀ FMT SCFA producer
🔴 Positive log₂FC Muribaculaceae (Bacteroidales) Aged♀ FMT SCFA producer
🔴 Positive log₂FC Desulfovibrionaceae (Desulfovibrionales) Aged♀ FMT Sulfate-reducing
🔵 Negative log₂FC Erysipelotrichaceae (Erysipelotrichales) Aged♂ FMT Pro-inflammatory association
🔵 Negative log₂FC Rikenellaceae (Bacteroidales) Aged♂ FMT Context-dependent
🔵 Negative log₂FC Clostridiales vadinBB60 group Aged♂ FMT Function unclear

⚠️ Note: This analysis uses DESeq2 on non-rarefied integer counts from ps_filt, with taxa prefiltered (total counts ≥10). Only taxa with Benjamini–Hochberg adjusted p < 0.05 are shown. The same ASVs/OTUs appear in Figure 4C and Supplementary Figure 4B, but Figure 5D specifically compares FMT recipient outcomes (Groups 9 vs. 10), not baseline donor differences.

🔹 Supplementary_Figure4=Figure4B-C: Aged Donors (Homeostatic)

“(A) Bray-Curtis distances between aged male-male, female-female and female-male stool samples under homeostatic conditions (nmale=8 and nfemale=6). (B) Cladogram showing differentially abundant OTUs…”

  • 👨 Aged male donors (n=8): Group4 → E1–E8 (E9, E10 excluded for low sequencing depth/outliers)
  • 👩 Aged female donors (n=6): Group3 → C1–C6 (C7–C10 excluded; C8–C9 younger mice, C10 outlier)

🔹 Figure 4B-C: Sex Differences in Aged Mice (16S rRNA-seq panels B–C)

“We profiled the gut bacterial composition of aged male and female mice by 16S rRNA-seq…”

  • Baseline aged female donors: Group3 → C1–C6
  • Baseline aged male donors: Group4 → E1–E8

(Note: Figure 4D–F show SCFA concentrations measured by targeted UHPLC-MS/MS, not 16S data.)

✅ PICRUSt2 NOT used in Figure 4D–F

Your observation is CORRECT: PICRUSt2 results are NOT used in Figure 4D–F.

Question Answer Evidence
Are PICRUSt2 results used in Figure 4? ❌ No Figure 4D–F legend explicitly states: “measured by targeted mass spectrometry”
Are PICRUSt2 results used anywhere in the manuscript? ❌ No evidence README_PICRUSt2.txt files contain exploratory pipeline notes, but no PICRUSt2 figures, tables, or text appear in 260311_LTPaper.pdf or 260310_Supplements.pdf
Is the SCFA data in Figure 4D–F experimentally measured? ✅ Yes Supplemental Methods (pages 12–13) describe UHPLC-MS/MS quantification with internal standards, derivatization, and MRM parameters

Key distinction:

  • PICRUSt2 → Predicts functional potential (gene/pathway abundances) from 16S sequences; outputs are relative, unitless values.
  • Figure 4D–F → Measures actual SCFA concentrations (acetate, butyrate, etc.) in µmol/l via targeted mass spectrometry; outputs are absolute, quantitative values.

Here is the merged quick reference table combining Figure 5B, 5C, and 5D with related figures, formatted for easy copy-paste:

🔹 Quick Reference: All Figure 5 Panels vs. Related Figures

Figure Comparison Sample IDs (exact) n Purpose
Figure 4B-C Aged♀ vs. aged♂ donors (homeostatic) C1–C6 vs. E1–E8 6 vs. 8 Baseline sex differences in microbiota (DESeq2 bubble plot)
Suppl Fig 4B Same as Fig 4C C1–C6 vs. E1–E8 6 vs. 8 Phylogenetic context of differential taxa (cladogram)
Figure 5B Pre-FMT vs. post-FMT recipients (4-group PCoA) G1–G6, H1–H6, I1–I6 (pre-FMT); J1, J2, J3, J4, J10, J11 (aged♂ FMT); K1–K6 (aged♀ FMT); L2–L6 (young♂ FMT) 18, 6, 6, 5 PCoA: microbiome shift after FMT (Bray–Curtis)
Figure 5C Donors vs. recipients (5 boxplots, family-level) G1–G6, H1–H6, I1–I6 (pre-FMT); E1–E8 (aged♂ donors); C1–C6 (aged♀ donors); J1, J2, J3, J4, J10, J11 (aged♂ FMT); K1–K6 (aged♀ FMT) 18, 8, 6, 6, 6 Taxonomic composition: donors vs. recipients (relative abundance)
Figure 5D Aged♀ vs. aged♂ FMT recipients (DESeq2) K1–K6 vs. J1, J2, J3, J4, J10, J11 6 vs. 6 Effect of donor microbiota on recipient immune response (differential abundance)
Figure 5E Same recipients as Fig 5D (+ young♂ control) K1–K6 vs. J1, J2, J3, J4, J10, J11 (+ L2–L6) 6 vs. 6 (+5) IL-17A+ γδ T cells in brain post-FMT (flow cytometry)

🔹 Sample-ID Master List for Figure 5

Group # Description Sample Prefix Full IDs Used In
3 Aged female, baseline FMT donor sample-C* C1–C10 (C1–C6 used in Fig 4B-C, Suppl Fig 4, Fig 5C) Fig 4C, Suppl Fig 4, Fig 5C
4 Aged male, baseline FMT donor sample-E* E1–E10 (E1–E8 used in Fig 4B-C, Suppl Fig 4, Fig 5C) Fig 4B-C, Suppl Fig 4, Fig 5C
6 Aged male, pre-antibiotics FMT batch I sample-G* G1–G6 Fig 5B (purple), Fig 5C (Boxplot 1)
7 Aged female, pre-antibiotics FMT batch I sample-H* H1–H6 Fig 5B (purple), Fig 5C (Boxplot 1)
8 Young male, pre-antibiotics FMT batch II sample-I* I1–I6 Fig 5B (purple), Fig 5C (Boxplot 1)
9 Young male, post-FMT aged male stool sample-J* J1–J4, J10, J11 (J5–J9 excluded) Fig 5B (blue), Fig 5C (Boxplot 4), Fig 5D, Fig 5E
10 Young male, post-FMT aged female stool sample-K* K1–K6 Fig 5B (red), Fig 5C (Boxplot 5), Fig 5D, Fig 5E
11 Young male, post-FMT young male stool sample-L* L2–L6 (L1, L7–L15 excluded) Fig 5B (green), Fig 5E (not in Fig 5C/D)

🔹 Key Notes for Interpretation

  1. Figure 5B vs. 5C: Figure 5B shows beta-diversity (PCoA) of all FMT groups; Figure 5C shows taxonomic composition (boxplots) of donors + recipients. Group11 (young♂ FMT) is in 5B but not in 5C.
  2. Figure 5D: Uses DESeq2 on non-rarefied counts from ps_filt (taxa prefiltered: total counts ≥10). Only taxa with BH-adjusted p < 0.05 are shown.
  3. Figure 5E: Includes the same recipients as Fig 5D plus the young♂ FMT control group (Group11, L2–L6) for comparison of IL-17A+ γδ T cells.
  4. Sample exclusions: C7–C10, E9–E10, J5–J9, K7–K15, L1, L7–L15 were excluded for low depth, outliers, or QC reasons (see README files).

Let me know if you’d like me to:

  1. Export the exact DESeq2 results table for Figure 5D as CSV/Excel,
  2. Provide the R code snippet that generates the bubble plot for Figure 5D, or
  3. Draft the full email reply to your colleague with these merged tables integrated. 🎯

Draft Reply to M.

Subject: Re: Manuscript Review (Lines 276-348) & NCBI SRA Citation

Thank you for sending the manuscript and for the opportunity to review the specified sections. I have carefully reviewed lines 276–348 covering the microbiota composition analysis and FMT experiments.

✅ Text Review: Minor Corrections Suggested

I noticed a few minor typographical inconsistencies in the taxonomic nomenclature that may warrant correction before submission:

Line Current Text Suggested Correction
295 Muribaculae (order Bacteroidalis) Muribaculaceae (order Bacteroidales)
298 Ruminococcae Ruminococcaceae
334 Muribaculae Muribaculaceae

These appear to be minor spelling variations; please confirm if these align with your intended taxonomic references.

The scientific content, logic flow, and figure references (Fig. 4A–D, Fig. 5A–E) are clear and well-integrated with our analysis scripts (MicrobiotaProcess_Group3-4.R and MicrobiotaProcess_Group9_10_11_PreFMT.R).

🗂️ NCBI SRA Data Submission

Regarding the NCBI SRA citation:

  1. Data readiness: The 16S rRNA sequencing data (Group 3/4 and Group 9/10/11/pre-FMT) are processed and ready for upload.
  2. Next steps:
    • I can prepare the metadata table (sample IDs, Group, Sex_age, pre_post_stroke) in the format required by NCBI BioProject.
    • Once uploaded, we will receive a BioProject/BioSample accession number (e.g., PRJNAxxxxxx) to cite in the manuscript.
  3. Suggested placement for citation: 
    Dataset: 16S rRNA-seq data are deposited in the NCBI Sequence Read Archive (SRA) 
under BioProject accession number [TO BE ADDED].

If you confirm, I can proceed with preparing the submission files this week so we meet your timeline.

📅 Timeline

I am flexible and ready to assist with final revisions or SRA submission as needed. Please let me know the exact submission date once confirmed, and I will prioritize accordingly.

Thank you again, and I wish you a pleasant weekend as well!

Note for me: Before sending,:

  1. Double-check the taxonomic spellings against your reference database (SILVA/GTDB)
  2. Confirm whether Marius prefers to handle the SRA upload himself or delegate it
  3. Attach the prepared metadata template if you want to expedite the process

Would you like me to help draft the NCBI BioProject metadata table or refine any part of this reply?